Leaderboard

At the OS level, uninstall all third party codecs, if you have any, ASAP. Any codec sets that add webp codec to the OS (K-lite and the such). Also, I suggest to uninstall all VP8 codec iterations, since it's basically the same with webp. For example, the famous French VLC player doesn't need any codecs in the system, it has its own.

I can suggest, as a quick fix, to search chrome.dll and replace all occurrences of "webp,image" with "apng,image", without quotes. Use any HEX edit software, make a backup before! With this dirty, nasty hack, your browser supposed to not accept webp virus, though I don't know if the website you visit don't support any other formats, so test it and report here! You aren't losing anything, since it's a junk, low quality format, to begin with. And what are you gonna do? Please share your fears, suggestions, opinions. Check here: OLD (before the edit) image/avif,image/webp,image/apng,image/svg+xml,image/ NEW (after the edit) image/avif,image/apng,image/apng,image/svg+xml,image/ https://www.amiunique.org/fingerprint This will make you unique, so proceed with caution, good luck!

109.0.5414.165 x64 EXE (non-MSI) installer link

What does the test page tell you? Post the screenshot please. Did you disable Client Hints? After the edit it should be. image/avif,image/apng,image/apng,image/svg+xml,image/ It's the header which tells the sites what's your browser can accept.

someone is trying to binary patch newer chrome: https://github.com/Blaukovitch/GOOGLE_CHROME_Windows_7_CRACK and 109 branch for win7/server 2012(r2) got an update for webp fix as well: https://chromereleases.googleblog.com/2023/09/stable-channel-desktop-update.html

Hi, Dietmar. https://stackoverflow.com/questions/3014187/can-we-run-an-java-app-in-a-system-without-jre

Maybe I should've added a "/s".

A warning, yes that should be added. But more options will not be added. It's just a simple action like get used clusters and copy them. Adding exclusions would require complete MFT parsing, what I don't have the time to implement.

I tried Supermium, finally, well it's quite good, but not portable and writes BrowserMetrics info collecting. Open it with Hex, you will see. You know what, you're right! I'll stick to the ported Opera 97 and Ungoogled 111, apply the anti webp-crap patch to decrapify them, certainly. If you use Opera, don't forget to apply the patch against collecting info-spying, made by @D.Draker. https://msfn.org/board/topic/184249-chrome-110-based-opera-i-ported-it-to-vista/?do=findComment&comment=1238878

NHS Digital and NHS England already declared it to be "medium". https://digital.nhs.uk/cyber-alerts/2023/cc-4376 CVE-2023-4863 Threat ID: CC-4376 Threat Severity: Medium Published: 12 September 2023 2:03 PM

LOL Yeah I was as surprised as you when I saw that xD Anyway, all is well what ends well

Since MSFN’s membership is largely European, there is one thing that I should clarify: Do not jump to the conclusion that these government warnings about TikTok are having very much effect in the United States! I can hardly watch a talk show on TV without some celebrity mentioning their TikTok account! (It seems to me that Europeans take government warnings far more seriously than Americans do.) Anyway, it looks like TikTok is here to stay, for better or for worse (at least until the next fad comes along).

It'd be quite simple to create a portable version (in PAF format) of FxESR-102.15.1 Download https://sourceforge.net/projects/portableapps/files/Mozilla Firefox%2C Portable Ed./Mozilla Firefox ESR%2C Portable Edition 102.13.0/FirefoxPortableESR_102.13.0_German.paf.exe/download Install/extract it to a disk location of your own choosing. Navigate to .\PortableApps\FirefoxPortableESR\App\ The contents of directories "Firefox" (32-bit) & "Firefox64" (64-bit) would have to be deleted and substituted with the 102.15.1 ones. https://ftp.mozilla.org/pub/firefox/releases/102.15.1esr/win32/de/Firefox Setup 102.15.1esr.exe Download, extract with 7-zip; the contents of the extracted "core" dir should be placed inside the above "Firefox" dir https://ftp.mozilla.org/pub/firefox/releases/102.15.1esr/win64/de/Firefox Setup 102.15.1esr.exe Download, extract with 7-zip; the contents of the extracted "core" dir should be placed inside the above "Firefox64" dir You should be done! When you then invoke the portable PAF launcher (FirefoxPortable.exe), it should launch Fx-102.15.1-x86 (if on a x86 OS) or Fx-102.15.1-x64 if on a x64 OS... (Apologies for the OTs, but I, too, am responding to OTs, sort of ...). Kind regards ...

@roytam1 has already fixed this security vulnerability in his latest release of New Moon 28: Therefore, setting the pref image.webp.enabled to false is not really needed anymore.

Obviously don't use Windows gallery anymore, pick some old software without webp format, to browse pics on your PC/laptop. Then make that programme default, so you won't accidentally open webp with native windows tools. I use the famous German NERO 8 (yes very old, 2007 or so). It doesn't know what webp is, so If I click on webp, even without extension, it doesn't know what to do with it.

This is a good one. Maybe they should make the .ISO's with different colours. jaclaz

Here, all here. https://msfn.org/board/topic/185031-webp-virus-fears-nightmares-suggestions-or-exodus-from-the-internet/

My theory has been confirmed! Despite having quite literally all our Win10 machines installed with EN-US, someone installed the Win11 ones with EN-GB, so I grabbed an EN-GB ISO and it worked:

Of course not. Or you can just edit the accept header and throw out webp into the garbage, where it belongs..

dll library wrappers included in version 117 will be useful for backporting Chromium Framework/Embedded etc based software with closed source code

because it is chrome, not chromium.

Sure! And don't forget to switch to IDE mode, before the install.

Agree, and it's a nice overclocker board too.

This topic is not about OS differences, please make your own.

People warned you not waste time on 1511. Especially since they fixed the issue with chrome.

New build of BOC/UXP for XP! Test binary: MailNews Win32 https://o.rthost.win/boc-uxp/mailnews.win32-20230916-d0fd16ed-uxp-58a39ca8cb-xpmod.7z BNavigator Win32 https://o.rthost.win/boc-uxp/bnavigator.win32-20230916-d0fd16ed-uxp-58a39ca8cb-xpmod.7z source repo (excluding UXP): https://github.com/roytam1/boc-uxp/tree/custom * Notice: the profile prefix (i.e. parent folder names) are also changed since 2020-08-15 build, you may rename their names before using new binaries when updating from builds before 2020-08-15. -- New build of HBL-UXP for XP! Test binary: IceDove-UXP(mail) https://o.rthost.win/hbl-uxp/icedove.win32-20230916-id-656ea98-uxp-58a39ca8cb-xpmod.7z IceApe-UXP(suite) https://o.rthost.win/hbl-uxp/iceape.win32-20230916-id-656ea98-ia-93af9a0-uxp-58a39ca8cb-xpmod.7z My repo changes: - packager: fix packaging when MOZ_GMP is not set (695d9d1) source repo (excluding UXP): https://github.com/roytam1/icedove-uxp/tree/winbuild https://github.com/roytam1/iceape-uxp/tree/winbuild for UXP changes please see above.

New build of Serpent/UXP for XP! Test binary: Win32 https://o.rthost.win/basilisk/basilisk52-g4.8.win32-git-20230916-3219d2d-uxp-58a39ca8cb-xpmod.7z Win64 https://o.rthost.win/basilisk/basilisk52-g4.8.win64-git-20230916-3219d2d-uxp-58a39ca8cb-xpmod.7z source code that is comparable to my current working tree is available here: https://github.com/roytam1/UXP/commits/custom IA32 Win32 https://o.rthost.win/basilisk/basilisk52-g4.8.win32-git-20230916-3219d2d-uxp-58a39ca8cb-xpmod-ia32.7z source code that is comparable to my current working tree is available here: https://github.com/roytam1/UXP/commits/ia32 NM28XP build: Win32 https://o.rthost.win/palemoon/palemoon-28.10.7a1.win32-git-20230916-d849524bd-uxp-58a39ca8cb-xpmod.7z Win32 IA32 https://o.rthost.win/palemoon/palemoon-28.10.7a1.win32-git-20230916-d849524bd-uxp-58a39ca8cb-xpmod-ia32.7z Win32 SSE https://o.rthost.win/palemoon/palemoon-28.10.7a1.win32-git-20230916-d849524bd-uxp-58a39ca8cb-xpmod-sse.7z Win64 https://o.rthost.win/palemoon/palemoon-28.10.7a1.win64-git-20230916-d849524bd-uxp-58a39ca8cb-xpmod.7z Official UXP changes picked since my last build: - Issue #2301 - Make Gecko Media Plugins optional when not building EME or WebRTC (9e7d1492e6) - Issue #2309 - Cherry-pick upstream libwebp fix. (20b69d7ddc) No official Pale-Moon changes picked since my last build. No official Basilisk changes picked since my last build. My changes picked since my last build: - [libwebp] Fix OOB write in BuildHuffmanTable. (61de658e45) - [libwebp] Fix invalid incremental decoding check. (3b44f9850e) - configure: move MOZ_GMP define block after MOZ_EME (f5cacdadbf) - dom/media: more eme fixes (58a39ca8cb) Update Notice: - You may delete file named icudt*.dat inside program folder when updating from old releases. * Notice: From now on, UXP rev will point to `custom` branch of my UXP repo instead of MCP UXP repo, while "official UXP changes" shows only `tracking` branch changes.

Asrock 775i65G seems nicer, though I's search for a mobo that supports FSB1333.

i Thanks Feodor2 - I'll look forward to the update. Right now, I've figured out a work around by finding the same articles on other websites.

Dixel's prediction has not yet come true. Just by replacing one missing function, Chromium 118 will still work on LTSB 2015 LOL I won't reveal the details for now, because someone from the Chromium team might read this and make for a spite in the next versions

Yep, crystal ball (when properly tuned) is far more accurate, but with i-ching, I asked how will the evolution of Chrome be and I got #12: http://the-iching.com/hexagram_12 not bad at all. jaclaz

Yeah, I agree with you. There are plenty of Windows 10 releases and even driver manufactors like Intel always increase their minimum system requirement to the latest 2 or 3 versions of Windows 10. My i5 8250U was released in 2017 and couldn't run anything below 1703 as far as I remember (with modified drivers only). I am also curious if the upcming Intel 14th Gen processors will even offer Windows 10 support anymore, since 13th Gen was already 21H2 and up only. We also have company based apps that get revised annualy and always increase their system requirements between Windows 10 versions. Edit: I tested Chromium 118 on 1607 and it works well. They implemented a function that was introduced with Server 2016/14393

Vista was fine. Just ahead of it's time with the system requirements. To me, Vista was the best looking Windows ever made. And with the proper hardware it ran rock solid, just like Windows 7. Win11 is the second best looking Windows imo. But I have had more broken OS problems after Windows 11 WU runs. I disliked the messy UI of Windows 10 so I stayed with Windows 7 until 11 came out. Windows 11 will probably get one or two big updates and then it is going to maintenance mode while new development will shift to Windows 12, or whatever the next Windows will be called.

Hi, there is binary test of to be a prime number or not. With 2 Hidden Layers it is hard to show. But with 3(!) Hidden Layers suddently you see something Dietmar PS: With more layers, it becomes even more clear that 1, 5, 7, 11, 13.. are the correct prime numbers, but 2 and 3 not. package hiddenlayers3; import org.apache.commons.math3.util.FastMath; import java.security.SecureRandom; public class HiddenLayers3 { private final int numInputNodes = 9; private final int numHiddenNodes1 = 12; private final int numHiddenNodes2 = 12; private final int numHiddenNodes3 = 12; private final int numOutputNodes = 1; private final double learningRate = 0.0003; private final int numEpochs = 100000; private final double errorThreshold = 0.00000000001; private double[][] inputToHidden1Weights; private double[][] hidden1ToHidden2Weights; private double[][] hidden2ToHidden3Weights; private double[][] hidden3ToOutputWeights; private double[] hidden1Biases; private double[] hidden2Biases; private double[] hidden3Biases; private double[] outputBiases; public HiddenLayers3() { SecureRandom random = new SecureRandom(); inputToHidden1Weights = new double[numInputNodes][numHiddenNodes1]; hidden1ToHidden2Weights = new double[numHiddenNodes1][numHiddenNodes2]; hidden2ToHidden3Weights = new double[numHiddenNodes2][numHiddenNodes3]; hidden3ToOutputWeights = new double[numHiddenNodes3][numOutputNodes]; hidden1Biases = new double[numHiddenNodes1]; hidden2Biases = new double[numHiddenNodes2]; hidden3Biases = new double[numHiddenNodes3]; outputBiases = new double[numOutputNodes]; for (int i = 0; i < numInputNodes; i++) { for (int j = 0; j < numHiddenNodes1; j++) { inputToHidden1Weights[i][j] = 0.3 * random.nextGaussian(); } } for (int i = 0; i < numHiddenNodes1; i++) { for (int j = 0; j < numHiddenNodes2; j++) { hidden1ToHidden2Weights[i][j] = 0.3 * random.nextGaussian(); } hidden1Biases[i] = 0.3 * random.nextGaussian(); } for (int i = 0; i < numHiddenNodes2; i++) { for (int j = 0; j < numHiddenNodes3; j++) { hidden2ToHidden3Weights[i][j] = 0.3 * random.nextGaussian(); } hidden2Biases[i] = 0.3 * random.nextGaussian(); } for (int i = 0; i < numHiddenNodes3; i++) { for (int j = 0; j < numOutputNodes; j++) { hidden3ToOutputWeights[i][j] = 0.3 * random.nextGaussian(); } hidden3Biases[i] = 0.3 * random.nextGaussian(); } for (int i = 0; i < numOutputNodes; i++) { outputBiases[i] = 0.3 * random.nextGaussian(); } } public double relu(double x) { return FastMath.max(0, x); } public double reluDerivative(double x) { return x > 0 ? 1 : 0; } public void train(double[][] trainingInputs, double[] trainingTargets) { for (int epoch = 1; epoch <= numEpochs; epoch++) { double totalError = 0.0; for (int i = 0; i < trainingInputs.length; i++) { // Skip excluded inputs if (i == 509) { continue; } double[] input = trainingInputs[i]; double target = trainingTargets[i]; // Forward propagation double[] hiddenOutputs1 = new double[numHiddenNodes1]; for (int j = 0; j < numHiddenNodes1; j++) { double weightedSum = 0.0; for (int k = 0; k < numInputNodes; k++) { weightedSum += inputToHidden1Weights[k][j] * input[k]; } hiddenOutputs1[j] = relu(weightedSum + hidden1Biases[j]); } double[] hiddenOutputs2 = new double[numHiddenNodes2]; for (int j = 0; j < numHiddenNodes2; j++) { double weightedSum = 0.0; for (int k = 0; k < numHiddenNodes1; k++) { weightedSum += hidden1ToHidden2Weights[k][j] * hiddenOutputs1[k]; } hiddenOutputs2[j] = relu(weightedSum + hidden2Biases[j]); } double[] hiddenOutputs3 = new double[numHiddenNodes3]; for (int j = 0; j < numHiddenNodes3; j++) { double weightedSum = 0.0; for (int k = 0; k < numHiddenNodes2; k++) { weightedSum += hidden2ToHidden3Weights[k][j] * hiddenOutputs2[k]; } hiddenOutputs3[j] = relu(weightedSum + hidden3Biases[j]); } double[] output = new double[numOutputNodes]; for (int j = 0; j < numOutputNodes; j++) { double weightedSum = 0.0; for (int k = 0; k < numHiddenNodes3; k++) { weightedSum += hidden3ToOutputWeights[k][j] * hiddenOutputs3[k]; } output[j] = relu(weightedSum + outputBiases[j]); } // Backward propagation double outputError = target - output[0]; double outputDelta = outputError * reluDerivative(output[0]); double[] hidden3Errors = new double[numHiddenNodes3]; double[] hidden3Deltas = new double[numHiddenNodes3]; for (int j = 0; j < numHiddenNodes3; j++) { double weightedSum = 0.0; for (int k = 0; k < numOutputNodes; k++) { weightedSum += hidden3ToOutputWeights[j][k] * outputDelta; } hidden3Errors[j] = weightedSum; hidden3Deltas[j] = hidden3Errors[j] * reluDerivative(hiddenOutputs3[j]); } double[] hidden2Errors = new double[numHiddenNodes2]; double[] hidden2Deltas = new double[numHiddenNodes2]; for (int j = 0; j < numHiddenNodes2; j++) { double weightedSum = 0.0; for (int k = 0; k < numHiddenNodes3; k++) { weightedSum += hidden2ToHidden3Weights[j][k] * hidden3Deltas[k]; } hidden2Errors[j] = weightedSum; hidden2Deltas[j] = hidden2Errors[j] * reluDerivative(hiddenOutputs2[j]); } double[] hidden1Errors = new double[numHiddenNodes1]; double[] hidden1Deltas = new double[numHiddenNodes1]; for (int j = 0; j < numHiddenNodes1; j++) { double weightedSum = 0.0; for (int k = 0; k < numHiddenNodes2; k++) { weightedSum += hidden1ToHidden2Weights[j][k] * hidden2Deltas[k]; } hidden1Errors[j] = weightedSum; hidden1Deltas[j] = hidden1Errors[j] * reluDerivative(hiddenOutputs1[j]); } // Update weights and biases for (int j = 0; j < numHiddenNodes3; j++) { for (int k = 0; k < numOutputNodes; k++) { hidden3ToOutputWeights[j][k] += learningRate * outputDelta * hiddenOutputs3[j]; } hidden3Biases[j] += learningRate * hidden3Deltas[j]; } for (int j = 0; j < numHiddenNodes2; j++) { for (int k = 0; k < numHiddenNodes3; k++) { hidden2ToHidden3Weights[j][k] += learningRate * hidden3Deltas[k] * hiddenOutputs2[j]; } hidden2Biases[j] += learningRate * hidden2Deltas[j]; } for (int j = 0; j < numHiddenNodes1; j++) { for (int k = 0; k < numHiddenNodes2; k++) { hidden1ToHidden2Weights[j][k] += learningRate * hidden2Deltas[k] * hiddenOutputs1[j]; } hidden1Biases[j] += learningRate * hidden1Deltas[j]; } for (int j = 0; j < numInputNodes; j++) { for (int k = 0; k < numHiddenNodes1; k++) { inputToHidden1Weights[j][k] += learningRate * hidden1Deltas[k] * input[j]; } } for (int j = 0; j < numOutputNodes; j++) { outputBiases[j] += learningRate * outputDelta; } // Calculate total error totalError += Math.pow(outputError, 2); } if (epoch % 2000 == 0) { System.out.println("Epoch " + epoch + ", Error: " + totalError); } if (totalError < errorThreshold) { System.out.println("Converged at epoch " + epoch); break; } } } public double predict(double[] input) { double[] hiddenOutputs1 = new double[numHiddenNodes1]; for (int j = 0; j < numHiddenNodes1; j++) { double weightedSum = 0.0; for (int k = 0; k < numInputNodes; k++) { weightedSum += inputToHidden1Weights[k][j] * input[k]; } hiddenOutputs1[j] = relu(weightedSum + hidden1Biases[j]); } double[] hiddenOutputs2 = new double[numHiddenNodes2]; for (int j = 0; j < numHiddenNodes2; j++) { double weightedSum = 0.0; for (int k = 0; k < numHiddenNodes1; k++) { weightedSum += hidden1ToHidden2Weights[k][j] * hiddenOutputs1[k]; } hiddenOutputs2[j] = relu(weightedSum + hidden2Biases[j]); } double[] hiddenOutputs3 = new double[numHiddenNodes3]; for (int j = 0; j < numHiddenNodes3; j++) { double weightedSum = 0.0; for (int k = 0; k < numHiddenNodes2; k++) { weightedSum += hidden2ToHidden3Weights[k][j] * hiddenOutputs2[k]; } hiddenOutputs3[j] = relu(weightedSum + hidden3Biases[j]); } double[] output = new double[numOutputNodes]; for (int j = 0; j < numOutputNodes; j++) { double weightedSum = 0.0; for (int k = 0; k < numHiddenNodes3; k++) { weightedSum += hidden3ToOutputWeights[k][j] * hiddenOutputs3[k]; } output[j] = relu(weightedSum + outputBiases[j]); } return output[0]; } public static void main(String[] args) { // Example usage of the neural network double[][] trainingInputs = { {0, 0, 0, 0, 0, 0, 0, 0, 0}, {0, 0, 0, 0, 0, 0, 0, 0, 1}, {0, 0, 0, 0, 0, 0, 0, 1, 0}, {0, 0, 0, 0, 0, 0, 0, 1, 1}, {0, 0, 0, 0, 0, 0, 1, 0, 0}, {0, 0, 0, 0, 0, 0, 1, 0, 1}, {0, 0, 0, 0, 0, 0, 1, 1, 0}, {0, 0, 0, 0, 0, 0, 1, 1, 1}, {0, 0, 0, 0, 0, 1, 0, 0, 0}, {0, 0, 0, 0, 0, 1, 0, 0, 1}, {0, 0, 0, 0, 0, 1, 0, 1, 0}, {0, 0, 0, 0, 0, 1, 0, 1, 1}, {0, 0, 0, 0, 0, 1, 1, 0, 0}, {0, 0, 0, 0, 0, 1, 1, 0, 1}, {0, 0, 0, 0, 0, 1, 1, 1, 0}, {0, 0, 0, 0, 0, 1, 1, 1, 1}, {0, 0, 0, 0, 1, 0, 0, 0, 0}, {0, 0, 0, 0, 1, 0, 0, 0, 1}, {0, 0, 0, 0, 1, 0, 0, 1, 0}, {0, 0, 0, 0, 1, 0, 0, 1, 1}, {0, 0, 0, 0, 1, 0, 1, 0, 0}, {0, 0, 0, 0, 1, 0, 1, 0, 1}, {0, 0, 0, 0, 1, 0, 1, 1, 0}, {0, 0, 0, 0, 1, 0, 1, 1, 1}, {0, 0, 0, 0, 1, 1, 0, 0, 0}, {0, 0, 0, 0, 1, 1, 0, 0, 1}, {0, 0, 0, 0, 1, 1, 0, 1, 0}, {0, 0, 0, 0, 1, 1, 0, 1, 1}, {0, 0, 0, 0, 1, 1, 1, 0, 0}, {0, 0, 0, 0, 1, 1, 1, 0, 1}, {0, 0, 0, 0, 1, 1, 1, 1, 0}, {0, 0, 0, 0, 1, 1, 1, 1, 1}, {0, 0, 0, 1, 0, 0, 0, 0, 0}, {0, 0, 0, 1, 0, 0, 0, 0, 1}, {0, 0, 0, 1, 0, 0, 0, 1, 0}, {0, 0, 0, 1, 0, 0, 0, 1, 1}, {0, 0, 0, 1, 0, 0, 1, 0, 0}, {0, 0, 0, 1, 0, 0, 1, 0, 1}, {0, 0, 0, 1, 0, 0, 1, 1, 0}, {0, 0, 0, 1, 0, 0, 1, 1, 1}, {0, 0, 0, 1, 0, 1, 0, 0, 0}, {0, 0, 0, 1, 0, 1, 0, 0, 1}, {0, 0, 0, 1, 0, 1, 0, 1, 0}, {0, 0, 0, 1, 0, 1, 0, 1, 1}, {0, 0, 0, 1, 0, 1, 1, 0, 0}, {0, 0, 0, 1, 0, 1, 1, 0, 1}, {0, 0, 0, 1, 0, 1, 1, 1, 0}, {0, 0, 0, 1, 0, 1, 1, 1, 1}, {0, 0, 0, 1, 1, 0, 0, 0, 0}, {0, 0, 0, 1, 1, 0, 0, 0, 1}, {0, 0, 0, 1, 1, 0, 0, 1, 0}, {0, 0, 0, 1, 1, 0, 0, 1, 1}, {0, 0, 0, 1, 1, 0, 1, 0, 0}, {0, 0, 0, 1, 1, 0, 1, 0, 1}, {0, 0, 0, 1, 1, 0, 1, 1, 0}, {0, 0, 0, 1, 1, 0, 1, 1, 1}, {0, 0, 0, 1, 1, 1, 0, 0, 0}, {0, 0, 0, 1, 1, 1, 0, 0, 1}, {0, 0, 0, 1, 1, 1, 0, 1, 0}, {0, 0, 0, 1, 1, 1, 0, 1, 1}, {0, 0, 0, 1, 1, 1, 1, 0, 0}, {0, 0, 0, 1, 1, 1, 1, 0, 1}, {0, 0, 0, 1, 1, 1, 1, 1, 0}, {0, 0, 0, 1, 1, 1, 1, 1, 1}, {0, 0, 1, 0, 0, 0, 0, 0, 0}, {0, 0, 1, 0, 0, 0, 0, 0, 1}, {0, 0, 1, 0, 0, 0, 0, 1, 0}, {0, 0, 1, 0, 0, 0, 0, 1, 1}, {0, 0, 1, 0, 0, 0, 1, 0, 0}, {0, 0, 1, 0, 0, 0, 1, 0, 1}, {0, 0, 1, 0, 0, 0, 1, 1, 0}, {0, 0, 1, 0, 0, 0, 1, 1, 1}, {0, 0, 1, 0, 0, 1, 0, 0, 0}, {0, 0, 1, 0, 0, 1, 0, 0, 1}, {0, 0, 1, 0, 0, 1, 0, 1, 0}, {0, 0, 1, 0, 0, 1, 0, 1, 1}, {0, 0, 1, 0, 0, 1, 1, 0, 0}, {0, 0, 1, 0, 0, 1, 1, 0, 1}, {0, 0, 1, 0, 0, 1, 1, 1, 0}, {0, 0, 1, 0, 0, 1, 1, 1, 1}, {0, 0, 1, 0, 1, 0, 0, 0, 0}, {0, 0, 1, 0, 1, 0, 0, 0, 1}, {0, 0, 1, 0, 1, 0, 0, 1, 0}, {0, 0, 1, 0, 1, 0, 0, 1, 1}, {0, 0, 1, 0, 1, 0, 1, 0, 0}, {0, 0, 1, 0, 1, 0, 1, 0, 1}, {0, 0, 1, 0, 1, 0, 1, 1, 0}, {0, 0, 1, 0, 1, 0, 1, 1, 1}, {0, 0, 1, 0, 1, 1, 0, 0, 0}, {0, 0, 1, 0, 1, 1, 0, 0, 1}, {0, 0, 1, 0, 1, 1, 0, 1, 0}, {0, 0, 1, 0, 1, 1, 0, 1, 1}, {0, 0, 1, 0, 1, 1, 1, 0, 0}, {0, 0, 1, 0, 1, 1, 1, 0, 1}, {0, 0, 1, 0, 1, 1, 1, 1, 0}, {0, 0, 1, 0, 1, 1, 1, 1, 1}, {0, 0, 1, 1, 0, 0, 0, 0, 0}, {0, 0, 1, 1, 0, 0, 0, 0, 1}, {0, 0, 1, 1, 0, 0, 0, 1, 0}, {0, 0, 1, 1, 0, 0, 0, 1, 1}, {0, 0, 1, 1, 0, 0, 1, 0, 0}, {0, 0, 1, 1, 0, 0, 1, 0, 1}, {0, 0, 1, 1, 0, 0, 1, 1, 0}, {0, 0, 1, 1, 0, 0, 1, 1, 1}, {0, 0, 1, 1, 0, 1, 0, 0, 0}, {0, 0, 1, 1, 0, 1, 0, 0, 1}, {0, 0, 1, 1, 0, 1, 0, 1, 0}, {0, 0, 1, 1, 0, 1, 0, 1, 1}, {0, 0, 1, 1, 0, 1, 1, 0, 0}, {0, 0, 1, 1, 0, 1, 1, 0, 1}, {0, 0, 1, 1, 0, 1, 1, 1, 0}, {0, 0, 1, 1, 0, 1, 1, 1, 1}, {0, 0, 1, 1, 1, 0, 0, 0, 0}, {0, 0, 1, 1, 1, 0, 0, 0, 1}, {0, 0, 1, 1, 1, 0, 0, 1, 0}, {0, 0, 1, 1, 1, 0, 0, 1, 1}, {0, 0, 1, 1, 1, 0, 1, 0, 0}, {0, 0, 1, 1, 1, 0, 1, 0, 1}, {0, 0, 1, 1, 1, 0, 1, 1, 0}, {0, 0, 1, 1, 1, 0, 1, 1, 1}, {0, 0, 1, 1, 1, 1, 0, 0, 0}, {0, 0, 1, 1, 1, 1, 0, 0, 1}, {0, 0, 1, 1, 1, 1, 0, 1, 0}, {0, 0, 1, 1, 1, 1, 0, 1, 1}, {0, 0, 1, 1, 1, 1, 1, 0, 0}, {0, 0, 1, 1, 1, 1, 1, 0, 1}, {0, 0, 1, 1, 1, 1, 1, 1, 0}, {0, 0, 1, 1, 1, 1, 1, 1, 1}, {0, 1, 0, 0, 0, 0, 0, 0, 0}, {0, 1, 0, 0, 0, 0, 0, 0, 1}, {0, 1, 0, 0, 0, 0, 0, 1, 0}, {0, 1, 0, 0, 0, 0, 0, 1, 1}, {0, 1, 0, 0, 0, 0, 1, 0, 0}, {0, 1, 0, 0, 0, 0, 1, 0, 1}, {0, 1, 0, 0, 0, 0, 1, 1, 0}, {0, 1, 0, 0, 0, 0, 1, 1, 1}, {0, 1, 0, 0, 0, 1, 0, 0, 0}, {0, 1, 0, 0, 0, 1, 0, 0, 1}, {0, 1, 0, 0, 0, 1, 0, 1, 0}, {0, 1, 0, 0, 0, 1, 0, 1, 1}, {0, 1, 0, 0, 0, 1, 1, 0, 0}, {0, 1, 0, 0, 0, 1, 1, 0, 1}, {0, 1, 0, 0, 0, 1, 1, 1, 0}, {0, 1, 0, 0, 0, 1, 1, 1, 1}, {0, 1, 0, 0, 1, 0, 0, 0, 0}, {0, 1, 0, 0, 1, 0, 0, 0, 1}, {0, 1, 0, 0, 1, 0, 0, 1, 0}, {0, 1, 0, 0, 1, 0, 0, 1, 1}, {0, 1, 0, 0, 1, 0, 1, 0, 0}, {0, 1, 0, 0, 1, 0, 1, 0, 1}, {0, 1, 0, 0, 1, 0, 1, 1, 0}, {0, 1, 0, 0, 1, 0, 1, 1, 1}, {0, 1, 0, 0, 1, 1, 0, 0, 0}, {0, 1, 0, 0, 1, 1, 0, 0, 1}, {0, 1, 0, 0, 1, 1, 0, 1, 0}, {0, 1, 0, 0, 1, 1, 0, 1, 1}, {0, 1, 0, 0, 1, 1, 1, 0, 0}, {0, 1, 0, 0, 1, 1, 1, 0, 1}, {0, 1, 0, 0, 1, 1, 1, 1, 0}, {0, 1, 0, 0, 1, 1, 1, 1, 1}, {0, 1, 0, 1, 0, 0, 0, 0, 0}, {0, 1, 0, 1, 0, 0, 0, 0, 1}, {0, 1, 0, 1, 0, 0, 0, 1, 0}, {0, 1, 0, 1, 0, 0, 0, 1, 1}, {0, 1, 0, 1, 0, 0, 1, 0, 0}, {0, 1, 0, 1, 0, 0, 1, 0, 1}, {0, 1, 0, 1, 0, 0, 1, 1, 0}, {0, 1, 0, 1, 0, 0, 1, 1, 1}, {0, 1, 0, 1, 0, 1, 0, 0, 0}, {0, 1, 0, 1, 0, 1, 0, 0, 1}, {0, 1, 0, 1, 0, 1, 0, 1, 0}, {0, 1, 0, 1, 0, 1, 0, 1, 1}, {0, 1, 0, 1, 0, 1, 1, 0, 0}, {0, 1, 0, 1, 0, 1, 1, 0, 1}, {0, 1, 0, 1, 0, 1, 1, 1, 0}, {0, 1, 0, 1, 0, 1, 1, 1, 1}, {0, 1, 0, 1, 1, 0, 0, 0, 0}, {0, 1, 0, 1, 1, 0, 0, 0, 1}, {0, 1, 0, 1, 1, 0, 0, 1, 0}, {0, 1, 0, 1, 1, 0, 0, 1, 1}, {0, 1, 0, 1, 1, 0, 1, 0, 0}, {0, 1, 0, 1, 1, 0, 1, 0, 1}, {0, 1, 0, 1, 1, 0, 1, 1, 0}, {0, 1, 0, 1, 1, 0, 1, 1, 1}, {0, 1, 0, 1, 1, 1, 0, 0, 0}, {0, 1, 0, 1, 1, 1, 0, 0, 1}, {0, 1, 0, 1, 1, 1, 0, 1, 0}, {0, 1, 0, 1, 1, 1, 0, 1, 1}, {0, 1, 0, 1, 1, 1, 1, 0, 0}, {0, 1, 0, 1, 1, 1, 1, 0, 1}, {0, 1, 0, 1, 1, 1, 1, 1, 0}, {0, 1, 0, 1, 1, 1, 1, 1, 1}, {0, 1, 1, 0, 0, 0, 0, 0, 0}, {0, 1, 1, 0, 0, 0, 0, 0, 1}, {0, 1, 1, 0, 0, 0, 0, 1, 0}, {0, 1, 1, 0, 0, 0, 0, 1, 1}, {0, 1, 1, 0, 0, 0, 1, 0, 0}, {0, 1, 1, 0, 0, 0, 1, 0, 1}, {0, 1, 1, 0, 0, 0, 1, 1, 0}, {0, 1, 1, 0, 0, 0, 1, 1, 1}, {0, 1, 1, 0, 0, 1, 0, 0, 0}, {0, 1, 1, 0, 0, 1, 0, 0, 1}, {0, 1, 1, 0, 0, 1, 0, 1, 0}, {0, 1, 1, 0, 0, 1, 0, 1, 1}, {0, 1, 1, 0, 0, 1, 1, 0, 0}, {0, 1, 1, 0, 0, 1, 1, 0, 1}, {0, 1, 1, 0, 0, 1, 1, 1, 0}, {0, 1, 1, 0, 0, 1, 1, 1, 1}, {0, 1, 1, 0, 1, 0, 0, 0, 0}, {0, 1, 1, 0, 1, 0, 0, 0, 1}, {0, 1, 1, 0, 1, 0, 0, 1, 0}, {0, 1, 1, 0, 1, 0, 0, 1, 1}, {0, 1, 1, 0, 1, 0, 1, 0, 0}, {0, 1, 1, 0, 1, 0, 1, 0, 1}, {0, 1, 1, 0, 1, 0, 1, 1, 0}, {0, 1, 1, 0, 1, 0, 1, 1, 1}, {0, 1, 1, 0, 1, 1, 0, 0, 0}, {0, 1, 1, 0, 1, 1, 0, 0, 1}, {0, 1, 1, 0, 1, 1, 0, 1, 0}, {0, 1, 1, 0, 1, 1, 0, 1, 1}, {0, 1, 1, 0, 1, 1, 1, 0, 0}, {0, 1, 1, 0, 1, 1, 1, 0, 1}, {0, 1, 1, 0, 1, 1, 1, 1, 0}, {0, 1, 1, 0, 1, 1, 1, 1, 1}, {0, 1, 1, 1, 0, 0, 0, 0, 0}, {0, 1, 1, 1, 0, 0, 0, 0, 1}, {0, 1, 1, 1, 0, 0, 0, 1, 0}, {0, 1, 1, 1, 0, 0, 0, 1, 1}, {0, 1, 1, 1, 0, 0, 1, 0, 0}, {0, 1, 1, 1, 0, 0, 1, 0, 1}, {0, 1, 1, 1, 0, 0, 1, 1, 0}, {0, 1, 1, 1, 0, 0, 1, 1, 1}, {0, 1, 1, 1, 0, 1, 0, 0, 0}, {0, 1, 1, 1, 0, 1, 0, 0, 1}, {0, 1, 1, 1, 0, 1, 0, 1, 0}, {0, 1, 1, 1, 0, 1, 0, 1, 1}, {0, 1, 1, 1, 0, 1, 1, 0, 0}, {0, 1, 1, 1, 0, 1, 1, 0, 1}, {0, 1, 1, 1, 0, 1, 1, 1, 0}, {0, 1, 1, 1, 0, 1, 1, 1, 1}, {0, 1, 1, 1, 1, 0, 0, 0, 0}, {0, 1, 1, 1, 1, 0, 0, 0, 1}, {0, 1, 1, 1, 1, 0, 0, 1, 0}, {0, 1, 1, 1, 1, 0, 0, 1, 1}, {0, 1, 1, 1, 1, 0, 1, 0, 0}, {0, 1, 1, 1, 1, 0, 1, 0, 1}, {0, 1, 1, 1, 1, 0, 1, 1, 0}, {0, 1, 1, 1, 1, 0, 1, 1, 1}, {0, 1, 1, 1, 1, 1, 0, 0, 0}, {0, 1, 1, 1, 1, 1, 0, 0, 1}, {0, 1, 1, 1, 1, 1, 0, 1, 0}, {0, 1, 1, 1, 1, 1, 0, 1, 1}, {0, 1, 1, 1, 1, 1, 1, 0, 0}, {0, 1, 1, 1, 1, 1, 1, 0, 1}, {0, 1, 1, 1, 1, 1, 1, 1, 0}, {0, 1, 1, 1, 1, 1, 1, 1, 1}, {1, 0, 0, 0, 0, 0, 0, 0, 0}, {1, 0, 0, 0, 0, 0, 0, 0, 1}, {1, 0, 0, 0, 0, 0, 0, 1, 0}, {1, 0, 0, 0, 0, 0, 0, 1, 1}, {1, 0, 0, 0, 0, 0, 1, 0, 0}, {1, 0, 0, 0, 0, 0, 1, 0, 1}, {1, 0, 0, 0, 0, 0, 1, 1, 0}, {1, 0, 0, 0, 0, 0, 1, 1, 1}, {1, 0, 0, 0, 0, 1, 0, 0, 0}, {1, 0, 0, 0, 0, 1, 0, 0, 1}, {1, 0, 0, 0, 0, 1, 0, 1, 0}, {1, 0, 0, 0, 0, 1, 0, 1, 1}, {1, 0, 0, 0, 0, 1, 1, 0, 0}, {1, 0, 0, 0, 0, 1, 1, 0, 1}, {1, 0, 0, 0, 0, 1, 1, 1, 0}, {1, 0, 0, 0, 0, 1, 1, 1, 1}, {1, 0, 0, 0, 1, 0, 0, 0, 0}, {1, 0, 0, 0, 1, 0, 0, 0, 1}, {1, 0, 0, 0, 1, 0, 0, 1, 0}, {1, 0, 0, 0, 1, 0, 0, 1, 1}, {1, 0, 0, 0, 1, 0, 1, 0, 0}, {1, 0, 0, 0, 1, 0, 1, 0, 1}, {1, 0, 0, 0, 1, 0, 1, 1, 0}, {1, 0, 0, 0, 1, 0, 1, 1, 1}, {1, 0, 0, 0, 1, 1, 0, 0, 0}, {1, 0, 0, 0, 1, 1, 0, 0, 1}, {1, 0, 0, 0, 1, 1, 0, 1, 0}, {1, 0, 0, 0, 1, 1, 0, 1, 1}, {1, 0, 0, 0, 1, 1, 1, 0, 0}, {1, 0, 0, 0, 1, 1, 1, 0, 1}, {1, 0, 0, 0, 1, 1, 1, 1, 0}, {1, 0, 0, 0, 1, 1, 1, 1, 1}, {1, 0, 0, 1, 0, 0, 0, 0, 0}, {1, 0, 0, 1, 0, 0, 0, 0, 1}, {1, 0, 0, 1, 0, 0, 0, 1, 0}, {1, 0, 0, 1, 0, 0, 0, 1, 1}, {1, 0, 0, 1, 0, 0, 1, 0, 0}, {1, 0, 0, 1, 0, 0, 1, 0, 1}, {1, 0, 0, 1, 0, 0, 1, 1, 0}, {1, 0, 0, 1, 0, 0, 1, 1, 1}, {1, 0, 0, 1, 0, 1, 0, 0, 0}, {1, 0, 0, 1, 0, 1, 0, 0, 1}, {1, 0, 0, 1, 0, 1, 0, 1, 0}, {1, 0, 0, 1, 0, 1, 0, 1, 1}, {1, 0, 0, 1, 0, 1, 1, 0, 0}, {1, 0, 0, 1, 0, 1, 1, 0, 1}, {1, 0, 0, 1, 0, 1, 1, 1, 0}, {1, 0, 0, 1, 0, 1, 1, 1, 1}, {1, 0, 0, 1, 1, 0, 0, 0, 0}, {1, 0, 0, 1, 1, 0, 0, 0, 1}, {1, 0, 0, 1, 1, 0, 0, 1, 0}, {1, 0, 0, 1, 1, 0, 0, 1, 1}, {1, 0, 0, 1, 1, 0, 1, 0, 0}, {1, 0, 0, 1, 1, 0, 1, 0, 1}, {1, 0, 0, 1, 1, 0, 1, 1, 0}, {1, 0, 0, 1, 1, 0, 1, 1, 1}, {1, 0, 0, 1, 1, 1, 0, 0, 0}, {1, 0, 0, 1, 1, 1, 0, 0, 1}, {1, 0, 0, 1, 1, 1, 0, 1, 0}, {1, 0, 0, 1, 1, 1, 0, 1, 1}, {1, 0, 0, 1, 1, 1, 1, 0, 0}, {1, 0, 0, 1, 1, 1, 1, 0, 1}, {1, 0, 0, 1, 1, 1, 1, 1, 0}, {1, 0, 0, 1, 1, 1, 1, 1, 1}, {1, 0, 1, 0, 0, 0, 0, 0, 0}, {1, 0, 1, 0, 0, 0, 0, 0, 1}, {1, 0, 1, 0, 0, 0, 0, 1, 0}, {1, 0, 1, 0, 0, 0, 0, 1, 1}, {1, 0, 1, 0, 0, 0, 1, 0, 0}, {1, 0, 1, 0, 0, 0, 1, 0, 1}, {1, 0, 1, 0, 0, 0, 1, 1, 0}, {1, 0, 1, 0, 0, 0, 1, 1, 1}, {1, 0, 1, 0, 0, 1, 0, 0, 0}, {1, 0, 1, 0, 0, 1, 0, 0, 1}, {1, 0, 1, 0, 0, 1, 0, 1, 0}, {1, 0, 1, 0, 0, 1, 0, 1, 1}, {1, 0, 1, 0, 0, 1, 1, 0, 0}, {1, 0, 1, 0, 0, 1, 1, 0, 1}, {1, 0, 1, 0, 0, 1, 1, 1, 0}, {1, 0, 1, 0, 0, 1, 1, 1, 1}, {1, 0, 1, 0, 1, 0, 0, 0, 0}, {1, 0, 1, 0, 1, 0, 0, 0, 1}, {1, 0, 1, 0, 1, 0, 0, 1, 0}, {1, 0, 1, 0, 1, 0, 0, 1, 1}, {1, 0, 1, 0, 1, 0, 1, 0, 0}, {1, 0, 1, 0, 1, 0, 1, 0, 1}, {1, 0, 1, 0, 1, 0, 1, 1, 0}, {1, 0, 1, 0, 1, 0, 1, 1, 1}, {1, 0, 1, 0, 1, 1, 0, 0, 0}, {1, 0, 1, 0, 1, 1, 0, 0, 1}, {1, 0, 1, 0, 1, 1, 0, 1, 0}, {1, 0, 1, 0, 1, 1, 0, 1, 1}, {1, 0, 1, 0, 1, 1, 1, 0, 0}, {1, 0, 1, 0, 1, 1, 1, 0, 1}, {1, 0, 1, 0, 1, 1, 1, 1, 0}, {1, 0, 1, 0, 1, 1, 1, 1, 1}, {1, 0, 1, 1, 0, 0, 0, 0, 0}, {1, 0, 1, 1, 0, 0, 0, 0, 1}, {1, 0, 1, 1, 0, 0, 0, 1, 0}, {1, 0, 1, 1, 0, 0, 0, 1, 1}, {1, 0, 1, 1, 0, 0, 1, 0, 0}, {1, 0, 1, 1, 0, 0, 1, 0, 1}, {1, 0, 1, 1, 0, 0, 1, 1, 0}, {1, 0, 1, 1, 0, 0, 1, 1, 1}, {1, 0, 1, 1, 0, 1, 0, 0, 0}, {1, 0, 1, 1, 0, 1, 0, 0, 1}, {1, 0, 1, 1, 0, 1, 0, 1, 0}, {1, 0, 1, 1, 0, 1, 0, 1, 1}, {1, 0, 1, 1, 0, 1, 1, 0, 0}, {1, 0, 1, 1, 0, 1, 1, 0, 1}, {1, 0, 1, 1, 0, 1, 1, 1, 0}, {1, 0, 1, 1, 0, 1, 1, 1, 1}, {1, 0, 1, 1, 1, 0, 0, 0, 0}, {1, 0, 1, 1, 1, 0, 0, 0, 1}, {1, 0, 1, 1, 1, 0, 0, 1, 0}, {1, 0, 1, 1, 1, 0, 0, 1, 1}, {1, 0, 1, 1, 1, 0, 1, 0, 0}, {1, 0, 1, 1, 1, 0, 1, 0, 1}, {1, 0, 1, 1, 1, 0, 1, 1, 0}, {1, 0, 1, 1, 1, 0, 1, 1, 1}, {1, 0, 1, 1, 1, 1, 0, 0, 0}, {1, 0, 1, 1, 1, 1, 0, 0, 1}, {1, 0, 1, 1, 1, 1, 0, 1, 0}, {1, 0, 1, 1, 1, 1, 0, 1, 1}, {1, 0, 1, 1, 1, 1, 1, 0, 0}, {1, 0, 1, 1, 1, 1, 1, 0, 1}, {1, 0, 1, 1, 1, 1, 1, 1, 0}, {1, 0, 1, 1, 1, 1, 1, 1, 1}, {1, 1, 0, 0, 0, 0, 0, 0, 0}, {1, 1, 0, 0, 0, 0, 0, 0, 1}, {1, 1, 0, 0, 0, 0, 0, 1, 0}, {1, 1, 0, 0, 0, 0, 0, 1, 1}, {1, 1, 0, 0, 0, 0, 1, 0, 0}, {1, 1, 0, 0, 0, 0, 1, 0, 1}, {1, 1, 0, 0, 0, 0, 1, 1, 0}, {1, 1, 0, 0, 0, 0, 1, 1, 1}, {1, 1, 0, 0, 0, 1, 0, 0, 0}, {1, 1, 0, 0, 0, 1, 0, 0, 1}, {1, 1, 0, 0, 0, 1, 0, 1, 0}, {1, 1, 0, 0, 0, 1, 0, 1, 1}, {1, 1, 0, 0, 0, 1, 1, 0, 0}, {1, 1, 0, 0, 0, 1, 1, 0, 1}, {1, 1, 0, 0, 0, 1, 1, 1, 0}, {1, 1, 0, 0, 0, 1, 1, 1, 1}, {1, 1, 0, 0, 1, 0, 0, 0, 0}, {1, 1, 0, 0, 1, 0, 0, 0, 1}, {1, 1, 0, 0, 1, 0, 0, 1, 0}, {1, 1, 0, 0, 1, 0, 0, 1, 1}, {1, 1, 0, 0, 1, 0, 1, 0, 0}, {1, 1, 0, 0, 1, 0, 1, 0, 1}, {1, 1, 0, 0, 1, 0, 1, 1, 0}, {1, 1, 0, 0, 1, 0, 1, 1, 1}, {1, 1, 0, 0, 1, 1, 0, 0, 0}, {1, 1, 0, 0, 1, 1, 0, 0, 1}, {1, 1, 0, 0, 1, 1, 0, 1, 0}, {1, 1, 0, 0, 1, 1, 0, 1, 1}, {1, 1, 0, 0, 1, 1, 1, 0, 0}, {1, 1, 0, 0, 1, 1, 1, 0, 1}, {1, 1, 0, 0, 1, 1, 1, 1, 0}, {1, 1, 0, 0, 1, 1, 1, 1, 1}, {1, 1, 0, 1, 0, 0, 0, 0, 0}, {1, 1, 0, 1, 0, 0, 0, 0, 1}, {1, 1, 0, 1, 0, 0, 0, 1, 0}, {1, 1, 0, 1, 0, 0, 0, 1, 1}, {1, 1, 0, 1, 0, 0, 1, 0, 0}, {1, 1, 0, 1, 0, 0, 1, 0, 1}, {1, 1, 0, 1, 0, 0, 1, 1, 0}, {1, 1, 0, 1, 0, 0, 1, 1, 1}, {1, 1, 0, 1, 0, 1, 0, 0, 0}, {1, 1, 0, 1, 0, 1, 0, 0, 1}, {1, 1, 0, 1, 0, 1, 0, 1, 0}, {1, 1, 0, 1, 0, 1, 0, 1, 1}, {1, 1, 0, 1, 0, 1, 1, 0, 0}, {1, 1, 0, 1, 0, 1, 1, 0, 1}, {1, 1, 0, 1, 0, 1, 1, 1, 0}, {1, 1, 0, 1, 0, 1, 1, 1, 1}, {1, 1, 0, 1, 1, 0, 0, 0, 0}, {1, 1, 0, 1, 1, 0, 0, 0, 1}, {1, 1, 0, 1, 1, 0, 0, 1, 0}, {1, 1, 0, 1, 1, 0, 0, 1, 1}, {1, 1, 0, 1, 1, 0, 1, 0, 0}, {1, 1, 0, 1, 1, 0, 1, 0, 1}, {1, 1, 0, 1, 1, 0, 1, 1, 0}, {1, 1, 0, 1, 1, 0, 1, 1, 1}, {1, 1, 0, 1, 1, 1, 0, 0, 0}, {1, 1, 0, 1, 1, 1, 0, 0, 1}, {1, 1, 0, 1, 1, 1, 0, 1, 0}, {1, 1, 0, 1, 1, 1, 0, 1, 1}, {1, 1, 0, 1, 1, 1, 1, 0, 0}, {1, 1, 0, 1, 1, 1, 1, 0, 1}, {1, 1, 0, 1, 1, 1, 1, 1, 0}, {1, 1, 0, 1, 1, 1, 1, 1, 1}, {1, 1, 1, 0, 0, 0, 0, 0, 0}, {1, 1, 1, 0, 0, 0, 0, 0, 1}, {1, 1, 1, 0, 0, 0, 0, 1, 0}, {1, 1, 1, 0, 0, 0, 0, 1, 1}, {1, 1, 1, 0, 0, 0, 1, 0, 0}, {1, 1, 1, 0, 0, 0, 1, 0, 1}, {1, 1, 1, 0, 0, 0, 1, 1, 0}, {1, 1, 1, 0, 0, 0, 1, 1, 1}, {1, 1, 1, 0, 0, 1, 0, 0, 0}, {1, 1, 1, 0, 0, 1, 0, 0, 1}, {1, 1, 1, 0, 0, 1, 0, 1, 0}, {1, 1, 1, 0, 0, 1, 0, 1, 1}, {1, 1, 1, 0, 0, 1, 1, 0, 0}, {1, 1, 1, 0, 0, 1, 1, 0, 1}, {1, 1, 1, 0, 0, 1, 1, 1, 0}, {1, 1, 1, 0, 0, 1, 1, 1, 1}, {1, 1, 1, 0, 1, 0, 0, 0, 0}, {1, 1, 1, 0, 1, 0, 0, 0, 1}, {1, 1, 1, 0, 1, 0, 0, 1, 0}, {1, 1, 1, 0, 1, 0, 0, 1, 1}, {1, 1, 1, 0, 1, 0, 1, 0, 0}, {1, 1, 1, 0, 1, 0, 1, 0, 1}, {1, 1, 1, 0, 1, 0, 1, 1, 0}, {1, 1, 1, 0, 1, 0, 1, 1, 1}, {1, 1, 1, 0, 1, 1, 0, 0, 0}, {1, 1, 1, 0, 1, 1, 0, 0, 1}, {1, 1, 1, 0, 1, 1, 0, 1, 0}, {1, 1, 1, 0, 1, 1, 0, 1, 1}, {1, 1, 1, 0, 1, 1, 1, 0, 0}, {1, 1, 1, 0, 1, 1, 1, 0, 1}, {1, 1, 1, 0, 1, 1, 1, 1, 0}, {1, 1, 1, 0, 1, 1, 1, 1, 1}, {1, 1, 1, 1, 0, 0, 0, 0, 0}, {1, 1, 1, 1, 0, 0, 0, 0, 1}, {1, 1, 1, 1, 0, 0, 0, 1, 0}, {1, 1, 1, 1, 0, 0, 0, 1, 1}, {1, 1, 1, 1, 0, 0, 1, 0, 0}, {1, 1, 1, 1, 0, 0, 1, 0, 1}, {1, 1, 1, 1, 0, 0, 1, 1, 0}, {1, 1, 1, 1, 0, 0, 1, 1, 1}, {1, 1, 1, 1, 0, 1, 0, 0, 0}, {1, 1, 1, 1, 0, 1, 0, 0, 1}, {1, 1, 1, 1, 0, 1, 0, 1, 0}, {1, 1, 1, 1, 0, 1, 0, 1, 1}, {1, 1, 1, 1, 0, 1, 1, 0, 0}, {1, 1, 1, 1, 0, 1, 1, 0, 1}, {1, 1, 1, 1, 0, 1, 1, 1, 0}, {1, 1, 1, 1, 0, 1, 1, 1, 1}, {1, 1, 1, 1, 1, 0, 0, 0, 0}, {1, 1, 1, 1, 1, 0, 0, 0, 1}, {1, 1, 1, 1, 1, 0, 0, 1, 0}, {1, 1, 1, 1, 1, 0, 0, 1, 1}, {1, 1, 1, 1, 1, 0, 1, 0, 0}, {1, 1, 1, 1, 1, 0, 1, 0, 1}, {1, 1, 1, 1, 1, 0, 1, 1, 0}, {1, 1, 1, 1, 1, 0, 1, 1, 1}, {1, 1, 1, 1, 1, 1, 0, 0, 0}, {1, 1, 1, 1, 1, 1, 0, 0, 1}, {1, 1, 1, 1, 1, 1, 0, 1, 0}, {1, 1, 1, 1, 1, 1, 0, 1, 1}, {1, 1, 1, 1, 1, 1, 1, 0, 0}, {1, 1, 1, 1, 1, 1, 1, 0, 1}, {1, 1, 1, 1, 1, 1, 1, 1, 0}, {1, 1, 1, 1, 1, 1, 1, 1, 1} }; double[] trainingTargets = { 0, 1, 0, 0, 0, 1, 0, 1, 0, 0, 0, 1, 0, 1, 0, 0, 0, 1, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 1, 0, 0, 0, 1, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1 , 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0 }; HiddenLayers3 nn = new HiddenLayers3(); nn.train(trainingInputs, trainingTargets); System.out.println("Prediction for [0, 0, 0, 0, 0, 0, 0, 0, 0]: " + nn.predict(new double[]{0, 0, 0, 0, 0, 0, 0, 0, 0})); System.out.println("Prediction for [0, 0, 0, 0, 0, 0, 0, 0, 1]: " + nn.predict(new double[]{0, 0, 0, 0, 0, 0, 0, 0, 1})); System.out.println("Prediction for [0, 0, 0, 0, 0, 0, 0, 1, 0]: " + nn.predict(new double[]{0, 0, 0, 0, 0, 0, 0, 1, 0})); System.out.println("Prediction for [0, 0, 0, 0, 0, 0, 0, 1, 1]: " + nn.predict(new double[]{0, 0, 0, 0, 0, 0, 0, 1, 1})); System.out.println("Prediction for [0, 0, 0, 0, 0, 0, 1, 0, 0]: " + nn.predict(new double[]{0, 0, 0, 0, 0, 0, 1, 0, 0})); System.out.println("Prediction for [0, 0, 0, 0, 0, 0, 1, 0, 1]: " + nn.predict(new double[]{0, 0, 0, 0, 0, 0, 1, 0, 1})); System.out.println("Prediction for [0, 0, 0, 0, 0, 0, 1, 1, 0]: " + nn.predict(new double[]{0, 0, 0, 0, 0, 0, 1, 1, 0})); System.out.println("Prediction for [0, 0, 0, 0, 0, 0, 1, 1, 1]: " + nn.predict(new double[]{0, 0, 0, 0, 0, 0, 1, 1, 1})); System.out.println("Prediction for [0, 0, 0, 0, 0, 1, 0, 0, 0]: " + nn.predict(new double[]{0, 0, 0, 0, 0, 1, 0, 0, 0})); System.out.println("Prediction for [0, 0, 0, 0, 0, 1, 0, 0, 1]: " + nn.predict(new double[]{0, 0, 0, 0, 0, 1, 0, 0, 1})); System.out.println("Prediction for [0, 0, 0, 0, 0, 1, 0, 1, 0]: " + nn.predict(new double[]{0, 0, 0, 0, 0, 1, 0, 1, 0})); System.out.println("Prediction for [0, 0, 0, 0, 0, 1, 0, 1, 1]: " + nn.predict(new double[]{0, 0, 0, 0, 0, 1, 0, 1, 1})); System.out.println("Prediction for [0, 0, 0, 0, 0, 1, 1, 0, 0]: " + nn.predict(new double[]{0, 0, 0, 0, 0, 1, 1, 0, 0})); System.out.println("Prediction for [0, 0, 0, 0, 0, 1, 1, 0, 1]: " + nn.predict(new double[]{0, 0, 0, 0, 0, 1, 1, 0, 1})); System.out.println("Prediction for [0, 0, 0, 0, 0, 1, 1, 1, 0]: " + nn.predict(new double[]{0, 0, 0, 0, 0, 1, 1, 1, 0})); System.out.println("Prediction for [0, 0, 0, 0, 0, 1, 1, 1, 1]: " + nn.predict(new double[]{0, 0, 0, 0, 0, 1, 1, 1, 1})); System.out.println("Prediction for [0, 0, 0, 0, 1, 0, 0, 0, 0]: " + nn.predict(new double[]{0, 0, 0, 0, 1, 0, 0, 0, 0})); System.out.println("Prediction for [0, 0, 0, 0, 1, 0, 0, 0, 1]: " + nn.predict(new double[]{0, 0, 0, 0, 1, 0, 0, 0, 1})); System.out.println("Prediction for [0, 0, 0, 0, 1, 0, 0, 1, 0]: " + nn.predict(new double[]{0, 0, 0, 0, 1, 0, 0, 1, 0})); System.out.println("Prediction for [0, 0, 0, 0, 1, 0, 0, 1, 1]: " + nn.predict(new double[]{0, 0, 0, 0, 1, 0, 0, 1, 1})); System.out.println("Prediction for [0, 0, 0, 0, 1, 0, 1, 0, 0]: " + nn.predict(new double[]{0, 0, 0, 0, 1, 0, 1, 0, 0})); System.out.println("Prediction for [0, 0, 0, 0, 1, 0, 1, 0, 1]: " + nn.predict(new double[]{0, 0, 0, 0, 1, 0, 1, 0, 1})); System.out.println("Prediction for [0, 0, 0, 0, 1, 0, 1, 1, 0]: " + nn.predict(new double[]{0, 0, 0, 0, 1, 0, 1, 1, 0})); System.out.println("Prediction for [0, 0, 0, 0, 1, 0, 1, 1, 1]: " + nn.predict(new double[]{0, 0, 0, 0, 1, 0, 1, 1, 1})); System.out.println("Prediction for [0, 0, 0, 0, 1, 1, 0, 0, 0]: " + nn.predict(new double[]{0, 0, 0, 0, 1, 1, 0, 0, 0})); System.out.println("Prediction for [0, 0, 0, 0, 1, 1, 0, 0, 1]: " + nn.predict(new double[]{0, 0, 0, 0, 1, 1, 0, 0, 1})); System.out.println("Prediction for [0, 0, 0, 0, 1, 1, 0, 1, 0]: " + nn.predict(new double[]{0, 0, 0, 0, 1, 1, 0, 1, 0})); System.out.println("Prediction for [0, 0, 0, 0, 1, 1, 0, 1, 1]: " + nn.predict(new double[]{0, 0, 0, 0, 1, 1, 0, 1, 1})); System.out.println("Prediction for [0, 0, 0, 0, 1, 1, 1, 0, 0]: " + nn.predict(new double[]{0, 0, 0, 0, 1, 1, 1, 0, 0})); System.out.println("Prediction for [0, 0, 0, 0, 1, 1, 1, 0, 1]: " + nn.predict(new double[]{0, 0, 0, 0, 1, 1, 1, 0, 1})); System.out.println("Prediction for [0, 0, 0, 0, 1, 1, 1, 1, 0]: " + nn.predict(new double[]{0, 0, 0, 0, 1, 1, 1, 1, 0})); System.out.println("Prediction for [0, 0, 0, 0, 1, 1, 1, 1, 1]: " + nn.predict(new double[]{0, 0, 0, 0, 1, 1, 1, 1, 1})); System.out.println("Prediction for [0, 0, 0, 1, 0, 0, 0, 0, 0]: " + nn.predict(new double[]{0, 0, 0, 1, 0, 0, 0, 0, 0})); System.out.println("Prediction for [0, 0, 0, 1, 0, 0, 0, 0, 1]: " + nn.predict(new double[]{0, 0, 0, 1, 0, 0, 0, 0, 1})); System.out.println("Prediction for [0, 0, 0, 1, 0, 0, 0, 1, 0]: " + nn.predict(new double[]{0, 0, 0, 1, 0, 0, 0, 1, 0})); System.out.println("Prediction for [0, 0, 0, 1, 0, 0, 0, 1, 1]: " + nn.predict(new double[]{0, 0, 0, 1, 0, 0, 0, 1, 1})); System.out.println("Prediction for [0, 0, 0, 1, 0, 0, 1, 0, 0]: " + nn.predict(new double[]{0, 0, 0, 1, 0, 0, 1, 0, 0})); System.out.println("Prediction for [0, 0, 0, 1, 0, 0, 1, 0, 1]: " + nn.predict(new double[]{0, 0, 0, 1, 0, 0, 1, 0, 1})); System.out.println("Prediction for [0, 0, 0, 1, 0, 0, 1, 1, 0]: " + nn.predict(new double[]{0, 0, 0, 1, 0, 0, 1, 1, 0})); System.out.println("Prediction for [0, 0, 0, 1, 0, 0, 1, 1, 1]: " + nn.predict(new double[]{0, 0, 0, 1, 0, 0, 1, 1, 1})); System.out.println("Prediction for [0, 0, 0, 1, 0, 1, 0, 0, 0]: " + nn.predict(new double[]{0, 0, 0, 1, 0, 1, 0, 0, 0})); System.out.println("Prediction for [0, 0, 0, 1, 0, 1, 0, 0, 1]: " + nn.predict(new double[]{0, 0, 0, 1, 0, 1, 0, 0, 1})); System.out.println("Prediction for [0, 0, 0, 1, 0, 1, 0, 1, 0]: " + nn.predict(new double[]{0, 0, 0, 1, 0, 1, 0, 1, 0})); System.out.println("Prediction for [0, 0, 0, 1, 0, 1, 0, 1, 1]: " + nn.predict(new double[]{0, 0, 0, 1, 0, 1, 0, 1, 1})); System.out.println("Prediction for [0, 0, 0, 1, 0, 1, 1, 0, 0]: " + nn.predict(new double[]{0, 0, 0, 1, 0, 1, 1, 0, 0})); System.out.println("Prediction for [0, 0, 0, 1, 0, 1, 1, 0, 1]: " + nn.predict(new double[]{0, 0, 0, 1, 0, 1, 1, 0, 1})); System.out.println("Prediction for [0, 0, 0, 1, 0, 1, 1, 1, 0]: " + nn.predict(new double[]{0, 0, 0, 1, 0, 1, 1, 1, 0})); System.out.println("Prediction for [0, 0, 0, 1, 0, 1, 1, 1, 1]: " + nn.predict(new double[]{0, 0, 0, 1, 0, 1, 1, 1, 1})); System.out.println("Prediction for [0, 0, 0, 1, 1, 0, 0, 0, 0]: " + nn.predict(new double[]{0, 0, 0, 1, 1, 0, 0, 0, 0})); System.out.println("Prediction for [0, 0, 0, 1, 1, 0, 0, 0, 1]: " + nn.predict(new double[]{0, 0, 0, 1, 1, 0, 0, 0, 1})); System.out.println("Prediction for [0, 0, 0, 1, 1, 0, 0, 1, 0]: " + nn.predict(new double[]{0, 0, 0, 1, 1, 0, 0, 1, 0})); System.out.println("Prediction for [0, 0, 0, 1, 1, 0, 0, 1, 1]: " + nn.predict(new double[]{0, 0, 0, 1, 1, 0, 0, 1, 1})); System.out.println("Prediction for [0, 0, 0, 1, 1, 0, 1, 0, 0]: " + nn.predict(new double[]{0, 0, 0, 1, 1, 0, 1, 0, 0})); System.out.println("Prediction for [0, 0, 0, 1, 1, 0, 1, 0, 1]: " + nn.predict(new double[]{0, 0, 0, 1, 1, 0, 1, 0, 1})); System.out.println("Prediction for [0, 0, 0, 1, 1, 0, 1, 1, 0]: " + nn.predict(new double[]{0, 0, 0, 1, 1, 0, 1, 1, 0})); System.out.println("Prediction for [0, 0, 0, 1, 1, 0, 1, 1, 1]: " + nn.predict(new double[]{0, 0, 0, 1, 1, 0, 1, 1, 1})); System.out.println("Prediction for [0, 0, 0, 1, 1, 1, 0, 0, 0]: " + nn.predict(new double[]{0, 0, 0, 1, 1, 1, 0, 0, 0})); System.out.println("Prediction for [0, 0, 0, 1, 1, 1, 0, 0, 1]: " + nn.predict(new double[]{0, 0, 0, 1, 1, 1, 0, 0, 1})); System.out.println("Prediction for [0, 0, 0, 1, 1, 1, 0, 1, 0]: " + nn.predict(new double[]{0, 0, 0, 1, 1, 1, 0, 1, 0})); System.out.println("Prediction for [0, 0, 0, 1, 1, 1, 0, 1, 1]: " + nn.predict(new double[]{0, 0, 0, 1, 1, 1, 0, 1, 1})); System.out.println("Prediction for [0, 0, 0, 1, 1, 1, 1, 0, 0]: " + nn.predict(new double[]{0, 0, 0, 1, 1, 1, 1, 0, 0})); System.out.println("Prediction for [0, 0, 0, 1, 1, 1, 1, 0, 1]: " + nn.predict(new double[]{0, 0, 0, 1, 1, 1, 1, 0, 1})); System.out.println("Prediction for [0, 0, 0, 1, 1, 1, 1, 1, 0]: " + nn.predict(new double[]{0, 0, 0, 1, 1, 1, 1, 1, 0})); System.out.println("Prediction for [0, 0, 0, 1, 1, 1, 1, 1, 1]: " + nn.predict(new double[]{0, 0, 0, 1, 1, 1, 1, 1, 1})); System.out.println("Prediction for [0, 0, 1, 0, 0, 0, 0, 0, 0]: " + nn.predict(new double[]{0, 0, 1, 0, 0, 0, 0, 0, 0})); System.out.println("Prediction for [0, 0, 1, 0, 0, 0, 0, 0, 1]: " + nn.predict(new double[]{0, 0, 1, 0, 0, 0, 0, 0, 1})); System.out.println("Prediction for [0, 0, 1, 0, 0, 0, 0, 1, 0]: " + nn.predict(new double[]{0, 0, 1, 0, 0, 0, 0, 1, 0})); System.out.println("Prediction for [0, 0, 1, 0, 0, 0, 0, 1, 1]: " + nn.predict(new double[]{0, 0, 1, 0, 0, 0, 0, 1, 1})); System.out.println("Prediction for [0, 0, 1, 0, 0, 0, 1, 0, 0]: " + nn.predict(new double[]{0, 0, 1, 0, 0, 0, 1, 0, 0})); System.out.println("Prediction for [0, 0, 1, 0, 0, 0, 1, 0, 1]: " + nn.predict(new double[]{0, 0, 1, 0, 0, 0, 1, 0, 1})); System.out.println("Prediction for [0, 0, 1, 0, 0, 0, 1, 1, 0]: " + nn.predict(new double[]{0, 0, 1, 0, 0, 0, 1, 1, 0})); System.out.println("Prediction for [0, 0, 1, 0, 0, 0, 1, 1, 1]: " + nn.predict(new double[]{0, 0, 1, 0, 0, 0, 1, 1, 1})); System.out.println("Prediction for [0, 0, 1, 0, 0, 1, 0, 0, 0]: " + nn.predict(new double[]{0, 0, 1, 0, 0, 1, 0, 0, 0})); System.out.println("Prediction for [0, 0, 1, 0, 0, 1, 0, 0, 1]: " + nn.predict(new double[]{0, 0, 1, 0, 0, 1, 0, 0, 1})); System.out.println("Prediction for [0, 0, 1, 0, 0, 1, 0, 1, 0]: " + nn.predict(new double[]{0, 0, 1, 0, 0, 1, 0, 1, 0})); System.out.println("Prediction for [0, 0, 1, 0, 0, 1, 0, 1, 1]: " + nn.predict(new double[]{0, 0, 1, 0, 0, 1, 0, 1, 1})); System.out.println("Prediction for [0, 0, 1, 0, 0, 1, 1, 0, 0]: " + nn.predict(new double[]{0, 0, 1, 0, 0, 1, 1, 0, 0})); System.out.println("Prediction for [0, 0, 1, 0, 0, 1, 1, 0, 1]: " + nn.predict(new double[]{0, 0, 1, 0, 0, 1, 1, 0, 1})); System.out.println("Prediction for [0, 0, 1, 0, 0, 1, 1, 1, 0]: " + nn.predict(new double[]{0, 0, 1, 0, 0, 1, 1, 1, 0})); System.out.println("Prediction for [0, 0, 1, 0, 0, 1, 1, 1, 1]: " + nn.predict(new double[]{0, 0, 1, 0, 0, 1, 1, 1, 1})); System.out.println("Prediction for [0, 0, 1, 0, 1, 0, 0, 0, 0]: " + nn.predict(new double[]{0, 0, 1, 0, 1, 0, 0, 0, 0})); System.out.println("Prediction for [0, 0, 1, 0, 1, 0, 0, 0, 1]: " + nn.predict(new double[]{0, 0, 1, 0, 1, 0, 0, 0, 1})); System.out.println("Prediction for [0, 0, 1, 0, 1, 0, 0, 1, 0]: " + nn.predict(new double[]{0, 0, 1, 0, 1, 0, 0, 1, 0})); System.out.println("Prediction for [0, 0, 1, 0, 1, 0, 0, 1, 1]: " + nn.predict(new double[]{0, 0, 1, 0, 1, 0, 0, 1, 1})); System.out.println("Prediction for [0, 0, 1, 0, 1, 0, 1, 0, 0]: " + nn.predict(new double[]{0, 0, 1, 0, 1, 0, 1, 0, 0})); System.out.println("Prediction for [0, 0, 1, 0, 1, 0, 1, 0, 1]: " + nn.predict(new double[]{0, 0, 1, 0, 1, 0, 1, 0, 1})); System.out.println("Prediction for [0, 0, 1, 0, 1, 0, 1, 1, 0]: " + nn.predict(new double[]{0, 0, 1, 0, 1, 0, 1, 1, 0})); System.out.println("Prediction for [0, 0, 1, 0, 1, 0, 1, 1, 1]: " + nn.predict(new double[]{0, 0, 1, 0, 1, 0, 1, 1, 1})); System.out.println("Prediction for [0, 0, 1, 0, 1, 1, 0, 0, 0]: " + nn.predict(new double[]{0, 0, 1, 0, 1, 1, 0, 0, 0})); System.out.println("Prediction for [0, 0, 1, 0, 1, 1, 0, 0, 1]: " + nn.predict(new double[]{0, 0, 1, 0, 1, 1, 0, 0, 1})); System.out.println("Prediction for [0, 0, 1, 0, 1, 1, 0, 1, 0]: " + nn.predict(new double[]{0, 0, 1, 0, 1, 1, 0, 1, 0})); System.out.println("Prediction for [0, 0, 1, 0, 1, 1, 0, 1, 1]: " + nn.predict(new double[]{0, 0, 1, 0, 1, 1, 0, 1, 1})); System.out.println("Prediction for [0, 0, 1, 0, 1, 1, 1, 0, 0]: " + nn.predict(new double[]{0, 0, 1, 0, 1, 1, 1, 0, 0})); System.out.println("Prediction for [0, 0, 1, 0, 1, 1, 1, 0, 1]: " + nn.predict(new double[]{0, 0, 1, 0, 1, 1, 1, 0, 1})); System.out.println("Prediction for [0, 0, 1, 0, 1, 1, 1, 1, 0]: " + nn.predict(new double[]{0, 0, 1, 0, 1, 1, 1, 1, 0})); System.out.println("Prediction for [0, 0, 1, 0, 1, 1, 1, 1, 1]: " + nn.predict(new double[]{0, 0, 1, 0, 1, 1, 1, 1, 1})); System.out.println("Prediction for [0, 0, 1, 1, 0, 0, 0, 0, 0]: " + nn.predict(new double[]{0, 0, 1, 1, 0, 0, 0, 0, 0})); System.out.println("Prediction for [0, 0, 1, 1, 0, 0, 0, 0, 1]: " + nn.predict(new double[]{0, 0, 1, 1, 0, 0, 0, 0, 1})); System.out.println("Prediction for [0, 0, 1, 1, 0, 0, 0, 1, 0]: " + nn.predict(new double[]{0, 0, 1, 1, 0, 0, 0, 1, 0})); System.out.println("Prediction for [0, 0, 1, 1, 0, 0, 0, 1, 1]: " + nn.predict(new double[]{0, 0, 1, 1, 0, 0, 0, 1, 1})); System.out.println("Prediction for [0, 0, 1, 1, 0, 0, 1, 0, 0]: " + nn.predict(new double[]{0, 0, 1, 1, 0, 0, 1, 0, 0})); System.out.println("Prediction for [0, 0, 1, 1, 0, 0, 1, 0, 1]: " + nn.predict(new double[]{0, 0, 1, 1, 0, 0, 1, 0, 1})); System.out.println("Prediction for [0, 0, 1, 1, 0, 0, 1, 1, 0]: " + nn.predict(new double[]{0, 0, 1, 1, 0, 0, 1, 1, 0})); System.out.println("Prediction for [0, 0, 1, 1, 0, 0, 1, 1, 1]: " + nn.predict(new double[]{0, 0, 1, 1, 0, 0, 1, 1, 1})); System.out.println("Prediction for [0, 0, 1, 1, 0, 1, 0, 0, 0]: " + nn.predict(new double[]{0, 0, 1, 1, 0, 1, 0, 0, 0})); System.out.println("Prediction for [0, 0, 1, 1, 0, 1, 0, 0, 1]: " + nn.predict(new double[]{0, 0, 1, 1, 0, 1, 0, 0, 1})); System.out.println("Prediction for [0, 0, 1, 1, 0, 1, 0, 1, 0]: " + nn.predict(new double[]{0, 0, 1, 1, 0, 1, 0, 1, 0})); System.out.println("Prediction for [0, 0, 1, 1, 0, 1, 0, 1, 1]: " + nn.predict(new double[]{0, 0, 1, 1, 0, 1, 0, 1, 1})); System.out.println("Prediction for [0, 0, 1, 1, 0, 1, 1, 0, 0]: " + nn.predict(new double[]{0, 0, 1, 1, 0, 1, 1, 0, 0})); System.out.println("Prediction for [0, 0, 1, 1, 0, 1, 1, 0, 1]: " + nn.predict(new double[]{0, 0, 1, 1, 0, 1, 1, 0, 1})); System.out.println("Prediction for [0, 0, 1, 1, 0, 1, 1, 1, 0]: " + nn.predict(new double[]{0, 0, 1, 1, 0, 1, 1, 1, 0})); System.out.println("Prediction for [0, 0, 1, 1, 0, 1, 1, 1, 1]: " + nn.predict(new double[]{0, 0, 1, 1, 0, 1, 1, 1, 1})); System.out.println("Prediction for [0, 0, 1, 1, 1, 0, 0, 0, 0]: " + nn.predict(new double[]{0, 0, 1, 1, 1, 0, 0, 0, 0})); System.out.println("Prediction for [0, 0, 1, 1, 1, 0, 0, 0, 1]: " + nn.predict(new double[]{0, 0, 1, 1, 1, 0, 0, 0, 1})); System.out.println("Prediction for [0, 0, 1, 1, 1, 0, 0, 1, 0]: " + nn.predict(new double[]{0, 0, 1, 1, 1, 0, 0, 1, 0})); System.out.println("Prediction for [0, 0, 1, 1, 1, 0, 0, 1, 1]: " + nn.predict(new double[]{0, 0, 1, 1, 1, 0, 0, 1, 1})); System.out.println("Prediction for [0, 0, 1, 1, 1, 0, 1, 0, 0]: " + nn.predict(new double[]{0, 0, 1, 1, 1, 0, 1, 0, 0})); System.out.println("Prediction for [0, 0, 1, 1, 1, 0, 1, 0, 1]: " + nn.predict(new double[]{0, 0, 1, 1, 1, 0, 1, 0, 1})); System.out.println("Prediction for [0, 0, 1, 1, 1, 0, 1, 1, 0]: " + nn.predict(new double[]{0, 0, 1, 1, 1, 0, 1, 1, 0})); System.out.println("Prediction for [0, 0, 1, 1, 1, 0, 1, 1, 1]: " + nn.predict(new double[]{0, 0, 1, 1, 1, 0, 1, 1, 1})); System.out.println("Prediction for [0, 0, 1, 1, 1, 1, 0, 0, 0]: " + nn.predict(new double[]{0, 0, 1, 1, 1, 1, 0, 0, 0})); System.out.println("Prediction for [0, 0, 1, 1, 1, 1, 0, 0, 1]: " + nn.predict(new double[]{0, 0, 1, 1, 1, 1, 0, 0, 1})); System.out.println("Prediction for [0, 0, 1, 1, 1, 1, 0, 1, 0]: " + nn.predict(new double[]{0, 0, 1, 1, 1, 1, 0, 1, 0})); System.out.println("Prediction for [0, 0, 1, 1, 1, 1, 0, 1, 1]: " + nn.predict(new double[]{0, 0, 1, 1, 1, 1, 0, 1, 1})); System.out.println("Prediction for [0, 0, 1, 1, 1, 1, 1, 0, 0]: " + nn.predict(new double[]{0, 0, 1, 1, 1, 1, 1, 0, 0})); System.out.println("Prediction for [0, 0, 1, 1, 1, 1, 1, 0, 1]: " + nn.predict(new double[]{0, 0, 1, 1, 1, 1, 1, 0, 1})); System.out.println("Prediction for [0, 0, 1, 1, 1, 1, 1, 1, 0]: " + nn.predict(new double[]{0, 0, 1, 1, 1, 1, 1, 1, 0})); System.out.println("Prediction for [0, 0, 1, 1, 1, 1, 1, 1, 1]: " + nn.predict(new double[]{0, 0, 1, 1, 1, 1, 1, 1, 1})); System.out.println("Prediction for [0, 1, 0, 0, 0, 0, 0, 0, 0]: " + nn.predict(new double[]{0, 1, 0, 0, 0, 0, 0, 0, 0})); System.out.println("Prediction for [0, 1, 0, 0, 0, 0, 0, 0, 1]: " + nn.predict(new double[]{0, 1, 0, 0, 0, 0, 0, 0, 1})); System.out.println("Prediction for [0, 1, 0, 0, 0, 0, 0, 1, 0]: " + nn.predict(new double[]{0, 1, 0, 0, 0, 0, 0, 1, 0})); System.out.println("Prediction for [0, 1, 0, 0, 0, 0, 0, 1, 1]: " + nn.predict(new double[]{0, 1, 0, 0, 0, 0, 0, 1, 1})); System.out.println("Prediction for [0, 1, 0, 0, 0, 0, 1, 0, 0]: " + nn.predict(new double[]{0, 1, 0, 0, 0, 0, 1, 0, 0})); System.out.println("Prediction for [0, 1, 0, 0, 0, 0, 1, 0, 1]: " + nn.predict(new double[]{0, 1, 0, 0, 0, 0, 1, 0, 1})); System.out.println("Prediction for [0, 1, 0, 0, 0, 0, 1, 1, 0]: " + nn.predict(new double[]{0, 1, 0, 0, 0, 0, 1, 1, 0})); System.out.println("Prediction for [0, 1, 0, 0, 0, 0, 1, 1, 1]: " + nn.predict(new double[]{0, 1, 0, 0, 0, 0, 1, 1, 1})); System.out.println("Prediction for [0, 1, 0, 0, 0, 1, 0, 0, 0]: " + nn.predict(new double[]{0, 1, 0, 0, 0, 1, 0, 0, 0})); System.out.println("Prediction for [0, 1, 0, 0, 0, 1, 0, 0, 1]: " + nn.predict(new double[]{0, 1, 0, 0, 0, 1, 0, 0, 1})); System.out.println("Prediction for [0, 1, 0, 0, 0, 1, 0, 1, 0]: " + nn.predict(new double[]{0, 1, 0, 0, 0, 1, 0, 1, 0})); System.out.println("Prediction for [0, 1, 0, 0, 0, 1, 0, 1, 1]: " + nn.predict(new double[]{0, 1, 0, 0, 0, 1, 0, 1, 1})); System.out.println("Prediction for [0, 1, 0, 0, 0, 1, 1, 0, 0]: " + nn.predict(new double[]{0, 1, 0, 0, 0, 1, 1, 0, 0})); System.out.println("Prediction for [0, 1, 0, 0, 0, 1, 1, 0, 1]: " + nn.predict(new double[]{0, 1, 0, 0, 0, 1, 1, 0, 1})); System.out.println("Prediction for [0, 1, 0, 0, 0, 1, 1, 1, 0]: " + nn.predict(new double[]{0, 1, 0, 0, 0, 1, 1, 1, 0})); System.out.println("Prediction for [0, 1, 0, 0, 0, 1, 1, 1, 1]: " + nn.predict(new double[]{0, 1, 0, 0, 0, 1, 1, 1, 1})); System.out.println("Prediction for [0, 1, 0, 0, 1, 0, 0, 0, 0]: " + nn.predict(new double[]{0, 1, 0, 0, 1, 0, 0, 0, 0})); System.out.println("Prediction for [0, 1, 0, 0, 1, 0, 0, 0, 1]: " + nn.predict(new double[]{0, 1, 0, 0, 1, 0, 0, 0, 1})); System.out.println("Prediction for [0, 1, 0, 0, 1, 0, 0, 1, 0]: " + nn.predict(new double[]{0, 1, 0, 0, 1, 0, 0, 1, 0})); System.out.println("Prediction for [0, 1, 0, 0, 1, 0, 0, 1, 1]: " + nn.predict(new double[]{0, 1, 0, 0, 1, 0, 0, 1, 1})); System.out.println("Prediction for [0, 1, 0, 0, 1, 0, 1, 0, 0]: " + nn.predict(new double[]{0, 1, 0, 0, 1, 0, 1, 0, 0})); System.out.println("Prediction for [0, 1, 0, 0, 1, 0, 1, 0, 1]: " + nn.predict(new double[]{0, 1, 0, 0, 1, 0, 1, 0, 1})); System.out.println("Prediction for [0, 1, 0, 0, 1, 0, 1, 1, 0]: " + nn.predict(new double[]{0, 1, 0, 0, 1, 0, 1, 1, 0})); System.out.println("Prediction for [0, 1, 0, 0, 1, 0, 1, 1, 1]: " + nn.predict(new double[]{0, 1, 0, 0, 1, 0, 1, 1, 1})); System.out.println("Prediction for [0, 1, 0, 0, 1, 1, 0, 0, 0]: " + nn.predict(new double[]{0, 1, 0, 0, 1, 1, 0, 0, 0})); System.out.println("Prediction for [0, 1, 0, 0, 1, 1, 0, 0, 1]: " + nn.predict(new double[]{0, 1, 0, 0, 1, 1, 0, 0, 1})); System.out.println("Prediction for [0, 1, 0, 0, 1, 1, 0, 1, 0]: " + nn.predict(new double[]{0, 1, 0, 0, 1, 1, 0, 1, 0})); System.out.println("Prediction for [0, 1, 0, 0, 1, 1, 0, 1, 1]: " + nn.predict(new double[]{0, 1, 0, 0, 1, 1, 0, 1, 1})); System.out.println("Prediction for [0, 1, 0, 0, 1, 1, 1, 0, 0]: " + nn.predict(new double[]{0, 1, 0, 0, 1, 1, 1, 0, 0})); System.out.println("Prediction for [0, 1, 0, 0, 1, 1, 1, 0, 1]: " + nn.predict(new double[]{0, 1, 0, 0, 1, 1, 1, 0, 1})); System.out.println("Prediction for [0, 1, 0, 0, 1, 1, 1, 1, 0]: " + nn.predict(new double[]{0, 1, 0, 0, 1, 1, 1, 1, 0})); System.out.println("Prediction for [0, 1, 0, 0, 1, 1, 1, 1, 1]: " + nn.predict(new double[]{0, 1, 0, 0, 1, 1, 1, 1, 1})); System.out.println("Prediction for [0, 1, 0, 1, 0, 0, 0, 0, 0]: " + nn.predict(new double[]{0, 1, 0, 1, 0, 0, 0, 0, 0})); System.out.println("Prediction for [0, 1, 0, 1, 0, 0, 0, 0, 1]: " + nn.predict(new double[]{0, 1, 0, 1, 0, 0, 0, 0, 1})); System.out.println("Prediction for [0, 1, 0, 1, 0, 0, 0, 1, 0]: " + nn.predict(new double[]{0, 1, 0, 1, 0, 0, 0, 1, 0})); System.out.println("Prediction for [0, 1, 0, 1, 0, 0, 0, 1, 1]: " + nn.predict(new double[]{0, 1, 0, 1, 0, 0, 0, 1, 1})); System.out.println("Prediction for [0, 1, 0, 1, 0, 0, 1, 0, 0]: " + nn.predict(new double[]{0, 1, 0, 1, 0, 0, 1, 0, 0})); System.out.println("Prediction for [0, 1, 0, 1, 0, 0, 1, 0, 1]: " + nn.predict(new double[]{0, 1, 0, 1, 0, 0, 1, 0, 1})); System.out.println("Prediction for [0, 1, 0, 1, 0, 0, 1, 1, 0]: " + nn.predict(new double[]{0, 1, 0, 1, 0, 0, 1, 1, 0})); System.out.println("Prediction for [0, 1, 0, 1, 0, 0, 1, 1, 1]: " + nn.predict(new double[]{0, 1, 0, 1, 0, 0, 1, 1, 1})); System.out.println("Prediction for [0, 1, 0, 1, 0, 1, 0, 0, 0]: " + nn.predict(new double[]{0, 1, 0, 1, 0, 1, 0, 0, 0})); System.out.println("Prediction for [0, 1, 0, 1, 0, 1, 0, 0, 1]: " + nn.predict(new double[]{0, 1, 0, 1, 0, 1, 0, 0, 1})); System.out.println("Prediction for [0, 1, 0, 1, 0, 1, 0, 1, 0]: " + nn.predict(new double[]{0, 1, 0, 1, 0, 1, 0, 1, 0})); System.out.println("Prediction for [0, 1, 0, 1, 0, 1, 0, 1, 1]: " + nn.predict(new double[]{0, 1, 0, 1, 0, 1, 0, 1, 1})); System.out.println("Prediction for [0, 1, 0, 1, 0, 1, 1, 0, 0]: " + nn.predict(new double[]{0, 1, 0, 1, 0, 1, 1, 0, 0})); System.out.println("Prediction for [0, 1, 0, 1, 0, 1, 1, 0, 1]: " + nn.predict(new double[]{0, 1, 0, 1, 0, 1, 1, 0, 1})); System.out.println("Prediction for [0, 1, 0, 1, 0, 1, 1, 1, 0]: " + nn.predict(new double[]{0, 1, 0, 1, 0, 1, 1, 1, 0})); System.out.println("Prediction for [0, 1, 0, 1, 0, 1, 1, 1, 1]: " + nn.predict(new double[]{0, 1, 0, 1, 0, 1, 1, 1, 1})); System.out.println("Prediction for [0, 1, 0, 1, 1, 0, 0, 0, 0]: " + nn.predict(new double[]{0, 1, 0, 1, 1, 0, 0, 0, 0})); System.out.println("Prediction for [0, 1, 0, 1, 1, 0, 0, 0, 1]: " + nn.predict(new double[]{0, 1, 0, 1, 1, 0, 0, 0, 1})); System.out.println("Prediction for [0, 1, 0, 1, 1, 0, 0, 1, 0]: " + nn.predict(new double[]{0, 1, 0, 1, 1, 0, 0, 1, 0})); System.out.println("Prediction for [0, 1, 0, 1, 1, 0, 0, 1, 1]: " + nn.predict(new double[]{0, 1, 0, 1, 1, 0, 0, 1, 1})); System.out.println("Prediction for [0, 1, 0, 1, 1, 0, 1, 0, 0]: " + nn.predict(new double[]{0, 1, 0, 1, 1, 0, 1, 0, 0})); System.out.println("Prediction for [0, 1, 0, 1, 1, 0, 1, 0, 1]: " + nn.predict(new double[]{0, 1, 0, 1, 1, 0, 1, 0, 1})); System.out.println("Prediction for [0, 1, 0, 1, 1, 0, 1, 1, 0]: " + nn.predict(new double[]{0, 1, 0, 1, 1, 0, 1, 1, 0})); System.out.println("Prediction for [0, 1, 0, 1, 1, 0, 1, 1, 1]: " + nn.predict(new double[]{0, 1, 0, 1, 1, 0, 1, 1, 1})); System.out.println("Prediction for [0, 1, 0, 1, 1, 1, 0, 0, 0]: " + nn.predict(new double[]{0, 1, 0, 1, 1, 1, 0, 0, 0})); System.out.println("Prediction for [0, 1, 0, 1, 1, 1, 0, 0, 1]: " + nn.predict(new double[]{0, 1, 0, 1, 1, 1, 0, 0, 1})); System.out.println("Prediction for [0, 1, 0, 1, 1, 1, 0, 1, 0]: " + nn.predict(new double[]{0, 1, 0, 1, 1, 1, 0, 1, 0})); System.out.println("Prediction for [0, 1, 0, 1, 1, 1, 0, 1, 1]: " + nn.predict(new double[]{0, 1, 0, 1, 1, 1, 0, 1, 1})); System.out.println("Prediction for [0, 1, 0, 1, 1, 1, 1, 0, 0]: " + nn.predict(new double[]{0, 1, 0, 1, 1, 1, 1, 0, 0})); System.out.println("Prediction for [0, 1, 0, 1, 1, 1, 1, 0, 1]: " + nn.predict(new double[]{0, 1, 0, 1, 1, 1, 1, 0, 1})); System.out.println("Prediction for [0, 1, 0, 1, 1, 1, 1, 1, 0]: " + nn.predict(new double[]{0, 1, 0, 1, 1, 1, 1, 1, 0})); System.out.println("Prediction for [0, 1, 0, 1, 1, 1, 1, 1, 1]: " + nn.predict(new double[]{0, 1, 0, 1, 1, 1, 1, 1, 1})); System.out.println("Prediction for [0, 1, 1, 0, 0, 0, 0, 0, 0]: " + nn.predict(new double[]{0, 1, 1, 0, 0, 0, 0, 0, 0})); System.out.println("Prediction for [0, 1, 1, 0, 0, 0, 0, 0, 1]: " + nn.predict(new double[]{0, 1, 1, 0, 0, 0, 0, 0, 1})); System.out.println("Prediction for [0, 1, 1, 0, 0, 0, 0, 1, 0]: " + nn.predict(new double[]{0, 1, 1, 0, 0, 0, 0, 1, 0})); System.out.println("Prediction for [0, 1, 1, 0, 0, 0, 0, 1, 1]: " + nn.predict(new double[]{0, 1, 1, 0, 0, 0, 0, 1, 1})); System.out.println("Prediction for [0, 1, 1, 0, 0, 0, 1, 0, 0]: " + nn.predict(new double[]{0, 1, 1, 0, 0, 0, 1, 0, 0})); System.out.println("Prediction for [0, 1, 1, 0, 0, 0, 1, 0, 1]: " + nn.predict(new double[]{0, 1, 1, 0, 0, 0, 1, 0, 1})); System.out.println("Prediction for [0, 1, 1, 0, 0, 0, 1, 1, 0]: " + nn.predict(new double[]{0, 1, 1, 0, 0, 0, 1, 1, 0})); System.out.println("Prediction for [0, 1, 1, 0, 0, 0, 1, 1, 1]: " + nn.predict(new double[]{0, 1, 1, 0, 0, 0, 1, 1, 1})); System.out.println("Prediction for [0, 1, 1, 0, 0, 1, 0, 0, 0]: " + nn.predict(new double[]{0, 1, 1, 0, 0, 1, 0, 0, 0})); System.out.println("Prediction for [0, 1, 1, 0, 0, 1, 0, 0, 1]: " + nn.predict(new double[]{0, 1, 1, 0, 0, 1, 0, 0, 1})); System.out.println("Prediction for [0, 1, 1, 0, 0, 1, 0, 1, 0]: " + nn.predict(new double[]{0, 1, 1, 0, 0, 1, 0, 1, 0})); System.out.println("Prediction for [0, 1, 1, 0, 0, 1, 0, 1, 1]: " + nn.predict(new double[]{0, 1, 1, 0, 0, 1, 0, 1, 1})); System.out.println("Prediction for [0, 1, 1, 0, 0, 1, 1, 0, 0]: " + nn.predict(new double[]{0, 1, 1, 0, 0, 1, 1, 0, 0})); System.out.println("Prediction for [0, 1, 1, 0, 0, 1, 1, 0, 1]: " + nn.predict(new double[]{0, 1, 1, 0, 0, 1, 1, 0, 1})); System.out.println("Prediction for [0, 1, 1, 0, 0, 1, 1, 1, 0]: " + nn.predict(new double[]{0, 1, 1, 0, 0, 1, 1, 1, 0})); System.out.println("Prediction for [0, 1, 1, 0, 0, 1, 1, 1, 1]: " + nn.predict(new double[]{0, 1, 1, 0, 0, 1, 1, 1, 1})); System.out.println("Prediction for [0, 1, 1, 0, 1, 0, 0, 0, 0]: " + nn.predict(new double[]{0, 1, 1, 0, 1, 0, 0, 0, 0})); System.out.println("Prediction for [0, 1, 1, 0, 1, 0, 0, 0, 1]: " + nn.predict(new double[]{0, 1, 1, 0, 1, 0, 0, 0, 1})); System.out.println("Prediction for [0, 1, 1, 0, 1, 0, 0, 1, 0]: " + nn.predict(new double[]{0, 1, 1, 0, 1, 0, 0, 1, 0})); System.out.println("Prediction for [0, 1, 1, 0, 1, 0, 0, 1, 1]: " + nn.predict(new double[]{0, 1, 1, 0, 1, 0, 0, 1, 1})); System.out.println("Prediction for [0, 1, 1, 0, 1, 0, 1, 0, 0]: " + nn.predict(new double[]{0, 1, 1, 0, 1, 0, 1, 0, 0})); System.out.println("Prediction for [0, 1, 1, 0, 1, 0, 1, 0, 1]: " + nn.predict(new double[]{0, 1, 1, 0, 1, 0, 1, 0, 1})); System.out.println("Prediction for [0, 1, 1, 0, 1, 0, 1, 1, 0]: " + nn.predict(new double[]{0, 1, 1, 0, 1, 0, 1, 1, 0})); System.out.println("Prediction for [0, 1, 1, 0, 1, 0, 1, 1, 1]: " + nn.predict(new double[]{0, 1, 1, 0, 1, 0, 1, 1, 1})); System.out.println("Prediction for [0, 1, 1, 0, 1, 1, 0, 0, 0]: " + nn.predict(new double[]{0, 1, 1, 0, 1, 1, 0, 0, 0})); System.out.println("Prediction for [0, 1, 1, 0, 1, 1, 0, 0, 1]: " + nn.predict(new double[]{0, 1, 1, 0, 1, 1, 0, 0, 1})); System.out.println("Prediction for [0, 1, 1, 0, 1, 1, 0, 1, 0]: " + nn.predict(new double[]{0, 1, 1, 0, 1, 1, 0, 1, 0})); System.out.println("Prediction for [0, 1, 1, 0, 1, 1, 0, 1, 1]: " + nn.predict(new double[]{0, 1, 1, 0, 1, 1, 0, 1, 1})); System.out.println("Prediction for [0, 1, 1, 0, 1, 1, 1, 0, 0]: " + nn.predict(new double[]{0, 1, 1, 0, 1, 1, 1, 0, 0})); System.out.println("Prediction for [0, 1, 1, 0, 1, 1, 1, 0, 1]: " + nn.predict(new double[]{0, 1, 1, 0, 1, 1, 1, 0, 1})); System.out.println("Prediction for [0, 1, 1, 0, 1, 1, 1, 1, 0]: " + nn.predict(new double[]{0, 1, 1, 0, 1, 1, 1, 1, 0})); System.out.println("Prediction for [0, 1, 1, 0, 1, 1, 1, 1, 1]: " + nn.predict(new double[]{0, 1, 1, 0, 1, 1, 1, 1, 1})); System.out.println("Prediction for [0, 1, 1, 1, 0, 0, 0, 0, 0]: " + nn.predict(new double[]{0, 1, 1, 1, 0, 0, 0, 0, 0})); System.out.println("Prediction for [0, 1, 1, 1, 0, 0, 0, 0, 1]: " + nn.predict(new double[]{0, 1, 1, 1, 0, 0, 0, 0, 1})); System.out.println("Prediction for [0, 1, 1, 1, 0, 0, 0, 1, 0]: " + nn.predict(new double[]{0, 1, 1, 1, 0, 0, 0, 1, 0})); System.out.println("Prediction for [0, 1, 1, 1, 0, 0, 0, 1, 1]: " + nn.predict(new double[]{0, 1, 1, 1, 0, 0, 0, 1, 1})); System.out.println("Prediction for [0, 1, 1, 1, 0, 0, 1, 0, 0]: " + nn.predict(new double[]{0, 1, 1, 1, 0, 0, 1, 0, 0})); System.out.println("Prediction for [0, 1, 1, 1, 0, 0, 1, 0, 1]: " + nn.predict(new double[]{0, 1, 1, 1, 0, 0, 1, 0, 1})); System.out.println("Prediction for [0, 1, 1, 1, 0, 0, 1, 1, 0]: " + nn.predict(new double[]{0, 1, 1, 1, 0, 0, 1, 1, 0})); System.out.println("Prediction for [0, 1, 1, 1, 0, 0, 1, 1, 1]: " + nn.predict(new double[]{0, 1, 1, 1, 0, 0, 1, 1, 1})); System.out.println("Prediction for [0, 1, 1, 1, 0, 1, 0, 0, 0]: " + nn.predict(new double[]{0, 1, 1, 1, 0, 1, 0, 0, 0})); System.out.println("Prediction for [0, 1, 1, 1, 0, 1, 0, 0, 1]: " + nn.predict(new double[]{0, 1, 1, 1, 0, 1, 0, 0, 1})); System.out.println("Prediction for [0, 1, 1, 1, 0, 1, 0, 1, 0]: " + nn.predict(new double[]{0, 1, 1, 1, 0, 1, 0, 1, 0})); System.out.println("Prediction for [0, 1, 1, 1, 0, 1, 0, 1, 1]: " + nn.predict(new double[]{0, 1, 1, 1, 0, 1, 0, 1, 1})); System.out.println("Prediction for [0, 1, 1, 1, 0, 1, 1, 0, 0]: " + nn.predict(new double[]{0, 1, 1, 1, 0, 1, 1, 0, 0})); System.out.println("Prediction for [0, 1, 1, 1, 0, 1, 1, 0, 1]: " + nn.predict(new double[]{0, 1, 1, 1, 0, 1, 1, 0, 1})); System.out.println("Prediction for [0, 1, 1, 1, 0, 1, 1, 1, 0]: " + nn.predict(new double[]{0, 1, 1, 1, 0, 1, 1, 1, 0})); System.out.println("Prediction for [0, 1, 1, 1, 0, 1, 1, 1, 1]: " + nn.predict(new double[]{0, 1, 1, 1, 0, 1, 1, 1, 1})); System.out.println("Prediction for [0, 1, 1, 1, 1, 0, 0, 0, 0]: " + nn.predict(new double[]{0, 1, 1, 1, 1, 0, 0, 0, 0})); System.out.println("Prediction for [0, 1, 1, 1, 1, 0, 0, 0, 1]: " + nn.predict(new double[]{0, 1, 1, 1, 1, 0, 0, 0, 1})); System.out.println("Prediction for [0, 1, 1, 1, 1, 0, 0, 1, 0]: " + nn.predict(new double[]{0, 1, 1, 1, 1, 0, 0, 1, 0})); System.out.println("Prediction for [0, 1, 1, 1, 1, 0, 0, 1, 1]: " + nn.predict(new double[]{0, 1, 1, 1, 1, 0, 0, 1, 1})); System.out.println("Prediction for [0, 1, 1, 1, 1, 0, 1, 0, 0]: " + nn.predict(new double[]{0, 1, 1, 1, 1, 0, 1, 0, 0})); System.out.println("Prediction for [0, 1, 1, 1, 1, 0, 1, 0, 1]: " + nn.predict(new double[]{0, 1, 1, 1, 1, 0, 1, 0, 1})); System.out.println("Prediction for [0, 1, 1, 1, 1, 0, 1, 1, 0]: " + nn.predict(new double[]{0, 1, 1, 1, 1, 0, 1, 1, 0})); System.out.println("Prediction for [0, 1, 1, 1, 1, 0, 1, 1, 1]: " + nn.predict(new double[]{0, 1, 1, 1, 1, 0, 1, 1, 1})); System.out.println("Prediction for [0, 1, 1, 1, 1, 1, 0, 0, 0]: " + nn.predict(new double[]{0, 1, 1, 1, 1, 1, 0, 0, 0})); System.out.println("Prediction for [0, 1, 1, 1, 1, 1, 0, 0, 1]: " + nn.predict(new double[]{0, 1, 1, 1, 1, 1, 0, 0, 1})); System.out.println("Prediction for [0, 1, 1, 1, 1, 1, 0, 1, 0]: " + nn.predict(new double[]{0, 1, 1, 1, 1, 1, 0, 1, 0})); System.out.println("Prediction for [0, 1, 1, 1, 1, 1, 0, 1, 1]: " + nn.predict(new double[]{0, 1, 1, 1, 1, 1, 0, 1, 1})); System.out.println("Prediction for [0, 1, 1, 1, 1, 1, 1, 0, 0]: " + nn.predict(new double[]{0, 1, 1, 1, 1, 1, 1, 0, 0})); System.out.println("Prediction for [0, 1, 1, 1, 1, 1, 1, 0, 1]: " + nn.predict(new double[]{0, 1, 1, 1, 1, 1, 1, 0, 1})); System.out.println("Prediction for [0, 1, 1, 1, 1, 1, 1, 1, 0]: " + nn.predict(new double[]{0, 1, 1, 1, 1, 1, 1, 1, 0})); System.out.println("Prediction for [0, 1, 1, 1, 1, 1, 1, 1, 1]: " + nn.predict(new double[]{0, 1, 1, 1, 1, 1, 1, 1, 1})); System.out.println("Prediction for [1, 0, 0, 0, 0, 0, 0, 0, 0]: " + nn.predict(new double[]{1, 0, 0, 0, 0, 0, 0, 0, 0})); System.out.println("Prediction for [1, 0, 0, 0, 0, 0, 0, 0, 1]: " + nn.predict(new double[]{1, 0, 0, 0, 0, 0, 0, 0, 1})); System.out.println("Prediction for [1, 0, 0, 0, 0, 0, 0, 1, 0]: " + nn.predict(new double[]{1, 0, 0, 0, 0, 0, 0, 1, 0})); System.out.println("Prediction for [1, 0, 0, 0, 0, 0, 0, 1, 1]: " + nn.predict(new double[]{1, 0, 0, 0, 0, 0, 0, 1, 1})); System.out.println("Prediction for [1, 0, 0, 0, 0, 0, 1, 0, 0]: " + nn.predict(new double[]{1, 0, 0, 0, 0, 0, 1, 0, 0})); System.out.println("Prediction for [1, 0, 0, 0, 0, 0, 1, 0, 1]: " + nn.predict(new double[]{1, 0, 0, 0, 0, 0, 1, 0, 1})); System.out.println("Prediction for [1, 0, 0, 0, 0, 0, 1, 1, 0]: " + nn.predict(new double[]{1, 0, 0, 0, 0, 0, 1, 1, 0})); System.out.println("Prediction for [1, 0, 0, 0, 0, 0, 1, 1, 1]: " + nn.predict(new double[]{1, 0, 0, 0, 0, 0, 1, 1, 1})); System.out.println("Prediction for [1, 0, 0, 0, 0, 1, 0, 0, 0]: " + nn.predict(new double[]{1, 0, 0, 0, 0, 1, 0, 0, 0})); System.out.println("Prediction for [1, 0, 0, 0, 0, 1, 0, 0, 1]: " + nn.predict(new double[]{1, 0, 0, 0, 0, 1, 0, 0, 1})); System.out.println("Prediction for [1, 0, 0, 0, 0, 1, 0, 1, 0]: " + nn.predict(new double[]{1, 0, 0, 0, 0, 1, 0, 1, 0})); System.out.println("Prediction for [1, 0, 0, 0, 0, 1, 0, 1, 1]: " + nn.predict(new double[]{1, 0, 0, 0, 0, 1, 0, 1, 1})); System.out.println("Prediction for [1, 0, 0, 0, 0, 1, 1, 0, 0]: " + nn.predict(new double[]{1, 0, 0, 0, 0, 1, 1, 0, 0})); System.out.println("Prediction for [1, 0, 0, 0, 0, 1, 1, 0, 1]: " + nn.predict(new double[]{1, 0, 0, 0, 0, 1, 1, 0, 1})); System.out.println("Prediction for [1, 0, 0, 0, 0, 1, 1, 1, 0]: " + nn.predict(new double[]{1, 0, 0, 0, 0, 1, 1, 1, 0})); System.out.println("Prediction for [1, 0, 0, 0, 0, 1, 1, 1, 1]: " + nn.predict(new double[]{1, 0, 0, 0, 0, 1, 1, 1, 1})); System.out.println("Prediction for [1, 0, 0, 0, 1, 0, 0, 0, 0]: " + nn.predict(new double[]{1, 0, 0, 0, 1, 0, 0, 0, 0})); System.out.println("Prediction for [1, 0, 0, 0, 1, 0, 0, 0, 1]: " + nn.predict(new double[]{1, 0, 0, 0, 1, 0, 0, 0, 1})); System.out.println("Prediction for [1, 0, 0, 0, 1, 0, 0, 1, 0]: " + nn.predict(new double[]{1, 0, 0, 0, 1, 0, 0, 1, 0})); System.out.println("Prediction for [1, 0, 0, 0, 1, 0, 0, 1, 1]: " + nn.predict(new double[]{1, 0, 0, 0, 1, 0, 0, 1, 1})); System.out.println("Prediction for [1, 0, 0, 0, 1, 0, 1, 0, 0]: " + nn.predict(new double[]{1, 0, 0, 0, 1, 0, 1, 0, 0})); System.out.println("Prediction for [1, 0, 0, 0, 1, 0, 1, 0, 1]: " + nn.predict(new double[]{1, 0, 0, 0, 1, 0, 1, 0, 1})); System.out.println("Prediction for [1, 0, 0, 0, 1, 0, 1, 1, 0]: " + nn.predict(new double[]{1, 0, 0, 0, 1, 0, 1, 1, 0})); System.out.println("Prediction for [1, 0, 0, 0, 1, 0, 1, 1, 1]: " + nn.predict(new double[]{1, 0, 0, 0, 1, 0, 1, 1, 1})); System.out.println("Prediction for [1, 0, 0, 0, 1, 1, 0, 0, 0]: " + nn.predict(new double[]{1, 0, 0, 0, 1, 1, 0, 0, 0})); System.out.println("Prediction for [1, 0, 0, 0, 1, 1, 0, 0, 1]: " + nn.predict(new double[]{1, 0, 0, 0, 1, 1, 0, 0, 1})); System.out.println("Prediction for [1, 0, 0, 0, 1, 1, 0, 1, 0]: " + nn.predict(new double[]{1, 0, 0, 0, 1, 1, 0, 1, 0})); System.out.println("Prediction for [1, 0, 0, 0, 1, 1, 0, 1, 1]: " + nn.predict(new double[]{1, 0, 0, 0, 1, 1, 0, 1, 1})); System.out.println("Prediction for [1, 0, 0, 0, 1, 1, 1, 0, 0]: " + nn.predict(new double[]{1, 0, 0, 0, 1, 1, 1, 0, 0})); System.out.println("Prediction for [1, 0, 0, 0, 1, 1, 1, 0, 1]: " + nn.predict(new double[]{1, 0, 0, 0, 1, 1, 1, 0, 1})); System.out.println("Prediction for [1, 0, 0, 0, 1, 1, 1, 1, 0]: " + nn.predict(new double[]{1, 0, 0, 0, 1, 1, 1, 1, 0})); System.out.println("Prediction for [1, 0, 0, 0, 1, 1, 1, 1, 1]: " + nn.predict(new double[]{1, 0, 0, 0, 1, 1, 1, 1, 1})); System.out.println("Prediction for [1, 0, 0, 1, 0, 0, 0, 0, 0]: " + nn.predict(new double[]{1, 0, 0, 1, 0, 0, 0, 0, 0})); System.out.println("Prediction for [1, 0, 0, 1, 0, 0, 0, 0, 1]: " + nn.predict(new double[]{1, 0, 0, 1, 0, 0, 0, 0, 1})); System.out.println("Prediction for [1, 0, 0, 1, 0, 0, 0, 1, 0]: " + nn.predict(new double[]{1, 0, 0, 1, 0, 0, 0, 1, 0})); System.out.println("Prediction for [1, 0, 0, 1, 0, 0, 0, 1, 1]: " + nn.predict(new double[]{1, 0, 0, 1, 0, 0, 0, 1, 1})); System.out.println("Prediction for [1, 0, 0, 1, 0, 0, 1, 0, 0]: " + nn.predict(new double[]{1, 0, 0, 1, 0, 0, 1, 0, 0})); System.out.println("Prediction for [1, 0, 0, 1, 0, 0, 1, 0, 1]: " + nn.predict(new double[]{1, 0, 0, 1, 0, 0, 1, 0, 1})); System.out.println("Prediction for [1, 0, 0, 1, 0, 0, 1, 1, 0]: " + nn.predict(new double[]{1, 0, 0, 1, 0, 0, 1, 1, 0})); System.out.println("Prediction for [1, 0, 0, 1, 0, 0, 1, 1, 1]: " + nn.predict(new double[]{1, 0, 0, 1, 0, 0, 1, 1, 1})); System.out.println("Prediction for [1, 0, 0, 1, 0, 1, 0, 0, 0]: " + nn.predict(new double[]{1, 0, 0, 1, 0, 1, 0, 0, 0})); System.out.println("Prediction for [1, 0, 0, 1, 0, 1, 0, 0, 1]: " + nn.predict(new double[]{1, 0, 0, 1, 0, 1, 0, 0, 1})); System.out.println("Prediction for [1, 0, 0, 1, 0, 1, 0, 1, 0]: " + nn.predict(new double[]{1, 0, 0, 1, 0, 1, 0, 1, 0})); System.out.println("Prediction for [1, 0, 0, 1, 0, 1, 0, 1, 1]: " + nn.predict(new double[]{1, 0, 0, 1, 0, 1, 0, 1, 1})); System.out.println("Prediction for [1, 0, 0, 1, 0, 1, 1, 0, 0]: " + nn.predict(new double[]{1, 0, 0, 1, 0, 1, 1, 0, 0})); System.out.println("Prediction for [1, 0, 0, 1, 0, 1, 1, 0, 1]: " + nn.predict(new double[]{1, 0, 0, 1, 0, 1, 1, 0, 1})); System.out.println("Prediction for [1, 0, 0, 1, 0, 1, 1, 1, 0]: " + nn.predict(new double[]{1, 0, 0, 1, 0, 1, 1, 1, 0})); System.out.println("Prediction for [1, 0, 0, 1, 0, 1, 1, 1, 1]: " + nn.predict(new double[]{1, 0, 0, 1, 0, 1, 1, 1, 1})); System.out.println("Prediction for [1, 0, 0, 1, 1, 0, 0, 0, 0]: " + nn.predict(new double[]{1, 0, 0, 1, 1, 0, 0, 0, 0})); System.out.println("Prediction for [1, 0, 0, 1, 1, 0, 0, 0, 1]: " + nn.predict(new double[]{1, 0, 0, 1, 1, 0, 0, 0, 1})); System.out.println("Prediction for [1, 0, 0, 1, 1, 0, 0, 1, 0]: " + nn.predict(new double[]{1, 0, 0, 1, 1, 0, 0, 1, 0})); System.out.println("Prediction for [1, 0, 0, 1, 1, 0, 0, 1, 1]: " + nn.predict(new double[]{1, 0, 0, 1, 1, 0, 0, 1, 1})); System.out.println("Prediction for [1, 0, 0, 1, 1, 0, 1, 0, 0]: " + nn.predict(new double[]{1, 0, 0, 1, 1, 0, 1, 0, 0})); System.out.println("Prediction for [1, 0, 0, 1, 1, 0, 1, 0, 1]: " + nn.predict(new double[]{1, 0, 0, 1, 1, 0, 1, 0, 1})); System.out.println("Prediction for [1, 0, 0, 1, 1, 0, 1, 1, 0]: " + nn.predict(new double[]{1, 0, 0, 1, 1, 0, 1, 1, 0})); System.out.println("Prediction for [1, 0, 0, 1, 1, 0, 1, 1, 1]: " + nn.predict(new double[]{1, 0, 0, 1, 1, 0, 1, 1, 1})); System.out.println("Prediction for [1, 0, 0, 1, 1, 1, 0, 0, 0]: " + nn.predict(new double[]{1, 0, 0, 1, 1, 1, 0, 0, 0})); System.out.println("Prediction for [1, 0, 0, 1, 1, 1, 0, 0, 1]: " + nn.predict(new double[]{1, 0, 0, 1, 1, 1, 0, 0, 1})); System.out.println("Prediction for [1, 0, 0, 1, 1, 1, 0, 1, 0]: " + nn.predict(new double[]{1, 0, 0, 1, 1, 1, 0, 1, 0})); System.out.println("Prediction for [1, 0, 0, 1, 1, 1, 0, 1, 1]: " + nn.predict(new double[]{1, 0, 0, 1, 1, 1, 0, 1, 1})); System.out.println("Prediction for [1, 0, 0, 1, 1, 1, 1, 0, 0]: " + nn.predict(new double[]{1, 0, 0, 1, 1, 1, 1, 0, 0})); System.out.println("Prediction for [1, 0, 0, 1, 1, 1, 1, 0, 1]: " + nn.predict(new double[]{1, 0, 0, 1, 1, 1, 1, 0, 1})); System.out.println("Prediction for [1, 0, 0, 1, 1, 1, 1, 1, 0]: " + nn.predict(new double[]{1, 0, 0, 1, 1, 1, 1, 1, 0})); System.out.println("Prediction for [1, 0, 0, 1, 1, 1, 1, 1, 1]: " + nn.predict(new double[]{1, 0, 0, 1, 1, 1, 1, 1, 1})); System.out.println("Prediction for [1, 0, 1, 0, 0, 0, 0, 0, 0]: " + nn.predict(new double[]{1, 0, 1, 0, 0, 0, 0, 0, 0})); System.out.println("Prediction for [1, 0, 1, 0, 0, 0, 0, 0, 1]: " + nn.predict(new double[]{1, 0, 1, 0, 0, 0, 0, 0, 1})); System.out.println("Prediction for [1, 0, 1, 0, 0, 0, 0, 1, 0]: " + nn.predict(new double[]{1, 0, 1, 0, 0, 0, 0, 1, 0})); System.out.println("Prediction for [1, 0, 1, 0, 0, 0, 0, 1, 1]: " + nn.predict(new double[]{1, 0, 1, 0, 0, 0, 0, 1, 1})); System.out.println("Prediction for [1, 0, 1, 0, 0, 0, 1, 0, 0]: " + nn.predict(new double[]{1, 0, 1, 0, 0, 0, 1, 0, 0})); System.out.println("Prediction for [1, 0, 1, 0, 0, 0, 1, 0, 1]: " + nn.predict(new double[]{1, 0, 1, 0, 0, 0, 1, 0, 1})); System.out.println("Prediction for [1, 0, 1, 0, 0, 0, 1, 1, 0]: " + nn.predict(new double[]{1, 0, 1, 0, 0, 0, 1, 1, 0})); System.out.println("Prediction for [1, 0, 1, 0, 0, 0, 1, 1, 1]: " + nn.predict(new double[]{1, 0, 1, 0, 0, 0, 1, 1, 1})); System.out.println("Prediction for [1, 0, 1, 0, 0, 1, 0, 0, 0]: " + nn.predict(new double[]{1, 0, 1, 0, 0, 1, 0, 0, 0})); System.out.println("Prediction for [1, 0, 1, 0, 0, 1, 0, 0, 1]: " + nn.predict(new double[]{1, 0, 1, 0, 0, 1, 0, 0, 1})); System.out.println("Prediction for [1, 0, 1, 0, 0, 1, 0, 1, 0]: " + nn.predict(new double[]{1, 0, 1, 0, 0, 1, 0, 1, 0})); System.out.println("Prediction for [1, 0, 1, 0, 0, 1, 0, 1, 1]: " + nn.predict(new double[]{1, 0, 1, 0, 0, 1, 0, 1, 1})); System.out.println("Prediction for [1, 0, 1, 0, 0, 1, 1, 0, 0]: " + nn.predict(new double[]{1, 0, 1, 0, 0, 1, 1, 0, 0})); System.out.println("Prediction for [1, 0, 1, 0, 0, 1, 1, 0, 1]: " + nn.predict(new double[]{1, 0, 1, 0, 0, 1, 1, 0, 1})); System.out.println("Prediction for [1, 0, 1, 0, 0, 1, 1, 1, 0]: " + nn.predict(new double[]{1, 0, 1, 0, 0, 1, 1, 1, 0})); System.out.println("Prediction for [1, 0, 1, 0, 0, 1, 1, 1, 1]: " + nn.predict(new double[]{1, 0, 1, 0, 0, 1, 1, 1, 1})); System.out.println("Prediction for [1, 0, 1, 0, 1, 0, 0, 0, 0]: " + nn.predict(new double[]{1, 0, 1, 0, 1, 0, 0, 0, 0})); System.out.println("Prediction for [1, 0, 1, 0, 1, 0, 0, 0, 1]: " + nn.predict(new double[]{1, 0, 1, 0, 1, 0, 0, 0, 1})); System.out.println("Prediction for [1, 0, 1, 0, 1, 0, 0, 1, 0]: " + nn.predict(new double[]{1, 0, 1, 0, 1, 0, 0, 1, 0})); System.out.println("Prediction for [1, 0, 1, 0, 1, 0, 0, 1, 1]: " + nn.predict(new double[]{1, 0, 1, 0, 1, 0, 0, 1, 1})); System.out.println("Prediction for [1, 0, 1, 0, 1, 0, 1, 0, 0]: " + nn.predict(new double[]{1, 0, 1, 0, 1, 0, 1, 0, 0})); System.out.println("Prediction for [1, 0, 1, 0, 1, 0, 1, 0, 1]: " + nn.predict(new double[]{1, 0, 1, 0, 1, 0, 1, 0, 1})); System.out.println("Prediction for [1, 0, 1, 0, 1, 0, 1, 1, 0]: " + nn.predict(new double[]{1, 0, 1, 0, 1, 0, 1, 1, 0})); System.out.println("Prediction for [1, 0, 1, 0, 1, 0, 1, 1, 1]: " + nn.predict(new double[]{1, 0, 1, 0, 1, 0, 1, 1, 1})); System.out.println("Prediction for [1, 0, 1, 0, 1, 1, 0, 0, 0]: " + nn.predict(new double[]{1, 0, 1, 0, 1, 1, 0, 0, 0})); System.out.println("Prediction for [1, 0, 1, 0, 1, 1, 0, 0, 1]: " + nn.predict(new double[]{1, 0, 1, 0, 1, 1, 0, 0, 1})); System.out.println("Prediction for [1, 0, 1, 0, 1, 1, 0, 1, 0]: " + nn.predict(new double[]{1, 0, 1, 0, 1, 1, 0, 1, 0})); System.out.println("Prediction for [1, 0, 1, 0, 1, 1, 0, 1, 1]: " + nn.predict(new double[]{1, 0, 1, 0, 1, 1, 0, 1, 1})); System.out.println("Prediction for [1, 0, 1, 0, 1, 1, 1, 0, 0]: " + nn.predict(new double[]{1, 0, 1, 0, 1, 1, 1, 0, 0})); System.out.println("Prediction for [1, 0, 1, 0, 1, 1, 1, 0, 1]: " + nn.predict(new double[]{1, 0, 1, 0, 1, 1, 1, 0, 1})); System.out.println("Prediction for [1, 0, 1, 0, 1, 1, 1, 1, 0]: " + nn.predict(new double[]{1, 0, 1, 0, 1, 1, 1, 1, 0})); System.out.println("Prediction for [1, 0, 1, 0, 1, 1, 1, 1, 1]: " + nn.predict(new double[]{1, 0, 1, 0, 1, 1, 1, 1, 1})); System.out.println("Prediction for [1, 0, 1, 1, 0, 0, 0, 0, 0]: " + nn.predict(new double[]{1, 0, 1, 1, 0, 0, 0, 0, 0})); System.out.println("Prediction for [1, 0, 1, 1, 0, 0, 0, 0, 1]: " + nn.predict(new double[]{1, 0, 1, 1, 0, 0, 0, 0, 1})); System.out.println("Prediction for [1, 0, 1, 1, 0, 0, 0, 1, 0]: " + nn.predict(new double[]{1, 0, 1, 1, 0, 0, 0, 1, 0})); System.out.println("Prediction for [1, 0, 1, 1, 0, 0, 0, 1, 1]: " + nn.predict(new double[]{1, 0, 1, 1, 0, 0, 0, 1, 1})); System.out.println("Prediction for [1, 0, 1, 1, 0, 0, 1, 0, 0]: " + nn.predict(new double[]{1, 0, 1, 1, 0, 0, 1, 0, 0})); System.out.println("Prediction for [1, 0, 1, 1, 0, 0, 1, 0, 1]: " + nn.predict(new double[]{1, 0, 1, 1, 0, 0, 1, 0, 1})); System.out.println("Prediction for [1, 0, 1, 1, 0, 0, 1, 1, 0]: " + nn.predict(new double[]{1, 0, 1, 1, 0, 0, 1, 1, 0})); System.out.println("Prediction for [1, 0, 1, 1, 0, 0, 1, 1, 1]: " + nn.predict(new double[]{1, 0, 1, 1, 0, 0, 1, 1, 1})); System.out.println("Prediction for [1, 0, 1, 1, 0, 1, 0, 0, 0]: " + nn.predict(new double[]{1, 0, 1, 1, 0, 1, 0, 0, 0})); System.out.println("Prediction for [1, 0, 1, 1, 0, 1, 0, 0, 1]: " + nn.predict(new double[]{1, 0, 1, 1, 0, 1, 0, 0, 1})); System.out.println("Prediction for [1, 0, 1, 1, 0, 1, 0, 1, 0]: " + nn.predict(new double[]{1, 0, 1, 1, 0, 1, 0, 1, 0})); System.out.println("Prediction for [1, 0, 1, 1, 0, 1, 0, 1, 1]: " + nn.predict(new double[]{1, 0, 1, 1, 0, 1, 0, 1, 1})); System.out.println("Prediction for [1, 0, 1, 1, 0, 1, 1, 0, 0]: " + nn.predict(new double[]{1, 0, 1, 1, 0, 1, 1, 0, 0})); System.out.println("Prediction for [1, 0, 1, 1, 0, 1, 1, 0, 1]: " + nn.predict(new double[]{1, 0, 1, 1, 0, 1, 1, 0, 1})); System.out.println("Prediction for [1, 0, 1, 1, 0, 1, 1, 1, 0]: " + nn.predict(new double[]{1, 0, 1, 1, 0, 1, 1, 1, 0})); System.out.println("Prediction for [1, 0, 1, 1, 0, 1, 1, 1, 1]: " + nn.predict(new double[]{1, 0, 1, 1, 0, 1, 1, 1, 1})); System.out.println("Prediction for [1, 0, 1, 1, 1, 0, 0, 0, 0]: " + nn.predict(new double[]{1, 0, 1, 1, 1, 0, 0, 0, 0})); System.out.println("Prediction for [1, 0, 1, 1, 1, 0, 0, 0, 1]: " + nn.predict(new double[]{1, 0, 1, 1, 1, 0, 0, 0, 1})); System.out.println("Prediction for [1, 0, 1, 1, 1, 0, 0, 1, 0]: " + nn.predict(new double[]{1, 0, 1, 1, 1, 0, 0, 1, 0})); System.out.println("Prediction for [1, 0, 1, 1, 1, 0, 0, 1, 1]: " + nn.predict(new double[]{1, 0, 1, 1, 1, 0, 0, 1, 1})); System.out.println("Prediction for [1, 0, 1, 1, 1, 0, 1, 0, 0]: " + nn.predict(new double[]{1, 0, 1, 1, 1, 0, 1, 0, 0})); System.out.println("Prediction for [1, 0, 1, 1, 1, 0, 1, 0, 1]: " + nn.predict(new double[]{1, 0, 1, 1, 1, 0, 1, 0, 1})); System.out.println("Prediction for [1, 0, 1, 1, 1, 0, 1, 1, 0]: " + nn.predict(new double[]{1, 0, 1, 1, 1, 0, 1, 1, 0})); System.out.println("Prediction for [1, 0, 1, 1, 1, 0, 1, 1, 1]: " + nn.predict(new double[]{1, 0, 1, 1, 1, 0, 1, 1, 1})); System.out.println("Prediction for [1, 0, 1, 1, 1, 1, 0, 0, 0]: " + nn.predict(new double[]{1, 0, 1, 1, 1, 1, 0, 0, 0})); System.out.println("Prediction for [1, 0, 1, 1, 1, 1, 0, 0, 1]: " + nn.predict(new double[]{1, 0, 1, 1, 1, 1, 0, 0, 1})); System.out.println("Prediction for [1, 0, 1, 1, 1, 1, 0, 1, 0]: " + nn.predict(new double[]{1, 0, 1, 1, 1, 1, 0, 1, 0})); System.out.println("Prediction for [1, 0, 1, 1, 1, 1, 0, 1, 1]: " + nn.predict(new double[]{1, 0, 1, 1, 1, 1, 0, 1, 1})); System.out.println("Prediction for [1, 0, 1, 1, 1, 1, 1, 0, 0]: " + nn.predict(new double[]{1, 0, 1, 1, 1, 1, 1, 0, 0})); System.out.println("Prediction for [1, 0, 1, 1, 1, 1, 1, 0, 1]: " + nn.predict(new double[]{1, 0, 1, 1, 1, 1, 1, 0, 1})); System.out.println("Prediction for [1, 0, 1, 1, 1, 1, 1, 1, 0]: " + nn.predict(new double[]{1, 0, 1, 1, 1, 1, 1, 1, 0})); System.out.println("Prediction for [1, 0, 1, 1, 1, 1, 1, 1, 1]: " + nn.predict(new double[]{1, 0, 1, 1, 1, 1, 1, 1, 1})); System.out.println("Prediction for [1, 1, 0, 0, 0, 0, 0, 0, 0]: " + nn.predict(new double[]{1, 1, 0, 0, 0, 0, 0, 0, 0})); System.out.println("Prediction for [1, 1, 0, 0, 0, 0, 0, 0, 1]: " + nn.predict(new double[]{1, 1, 0, 0, 0, 0, 0, 0, 1})); System.out.println("Prediction for [1, 1, 0, 0, 0, 0, 0, 1, 0]: " + nn.predict(new double[]{1, 1, 0, 0, 0, 0, 0, 1, 0})); System.out.println("Prediction for [1, 1, 0, 0, 0, 0, 0, 1, 1]: " + nn.predict(new double[]{1, 1, 0, 0, 0, 0, 0, 1, 1})); System.out.println("Prediction for [1, 1, 0, 0, 0, 0, 1, 0, 0]: " + nn.predict(new double[]{1, 1, 0, 0, 0, 0, 1, 0, 0})); System.out.println("Prediction for [1, 1, 0, 0, 0, 0, 1, 0, 1]: " + nn.predict(new double[]{1, 1, 0, 0, 0, 0, 1, 0, 1})); System.out.println("Prediction for [1, 1, 0, 0, 0, 0, 1, 1, 0]: " + nn.predict(new double[]{1, 1, 0, 0, 0, 0, 1, 1, 0})); System.out.println("Prediction for [1, 1, 0, 0, 0, 0, 1, 1, 1]: " + nn.predict(new double[]{1, 1, 0, 0, 0, 0, 1, 1, 1})); System.out.println("Prediction for [1, 1, 0, 0, 0, 1, 0, 0, 0]: " + nn.predict(new double[]{1, 1, 0, 0, 0, 1, 0, 0, 0})); System.out.println("Prediction for [1, 1, 0, 0, 0, 1, 0, 0, 1]: " + nn.predict(new double[]{1, 1, 0, 0, 0, 1, 0, 0, 1})); System.out.println("Prediction for [1, 1, 0, 0, 0, 1, 0, 1, 0]: " + nn.predict(new double[]{1, 1, 0, 0, 0, 1, 0, 1, 0})); System.out.println("Prediction for [1, 1, 0, 0, 0, 1, 0, 1, 1]: " + nn.predict(new double[]{1, 1, 0, 0, 0, 1, 0, 1, 1})); System.out.println("Prediction for [1, 1, 0, 0, 0, 1, 1, 0, 0]: " + nn.predict(new double[]{1, 1, 0, 0, 0, 1, 1, 0, 0})); System.out.println("Prediction for [1, 1, 0, 0, 0, 1, 1, 0, 1]: " + nn.predict(new double[]{1, 1, 0, 0, 0, 1, 1, 0, 1})); System.out.println("Prediction for [1, 1, 0, 0, 0, 1, 1, 1, 0]: " + nn.predict(new double[]{1, 1, 0, 0, 0, 1, 1, 1, 0})); System.out.println("Prediction for [1, 1, 0, 0, 0, 1, 1, 1, 1]: " + nn.predict(new double[]{1, 1, 0, 0, 0, 1, 1, 1, 1})); System.out.println("Prediction for [1, 1, 0, 0, 1, 0, 0, 0, 0]: " + nn.predict(new double[]{1, 1, 0, 0, 1, 0, 0, 0, 0})); System.out.println("Prediction for [1, 1, 0, 0, 1, 0, 0, 0, 1]: " + nn.predict(new double[]{1, 1, 0, 0, 1, 0, 0, 0, 1})); System.out.println("Prediction for [1, 1, 0, 0, 1, 0, 0, 1, 0]: " + nn.predict(new double[]{1, 1, 0, 0, 1, 0, 0, 1, 0})); System.out.println("Prediction for [1, 1, 0, 0, 1, 0, 0, 1, 1]: " + nn.predict(new double[]{1, 1, 0, 0, 1, 0, 0, 1, 1})); System.out.println("Prediction for [1, 1, 0, 0, 1, 0, 1, 0, 0]: " + nn.predict(new double[]{1, 1, 0, 0, 1, 0, 1, 0, 0})); System.out.println("Prediction for [1, 1, 0, 0, 1, 0, 1, 0, 1]: " + nn.predict(new double[]{1, 1, 0, 0, 1, 0, 1, 0, 1})); System.out.println("Prediction for [1, 1, 0, 0, 1, 0, 1, 1, 0]: " + nn.predict(new double[]{1, 1, 0, 0, 1, 0, 1, 1, 0})); System.out.println("Prediction for [1, 1, 0, 0, 1, 0, 1, 1, 1]: " + nn.predict(new double[]{1, 1, 0, 0, 1, 0, 1, 1, 1})); System.out.println("Prediction for [1, 1, 0, 0, 1, 1, 0, 0, 0]: " + nn.predict(new double[]{1, 1, 0, 0, 1, 1, 0, 0, 0})); System.out.println("Prediction for [1, 1, 0, 0, 1, 1, 0, 0, 1]: " + nn.predict(new double[]{1, 1, 0, 0, 1, 1, 0, 0, 1})); System.out.println("Prediction for [1, 1, 0, 0, 1, 1, 0, 1, 0]: " + nn.predict(new double[]{1, 1, 0, 0, 1, 1, 0, 1, 0})); System.out.println("Prediction for [1, 1, 0, 0, 1, 1, 0, 1, 1]: " + nn.predict(new double[]{1, 1, 0, 0, 1, 1, 0, 1, 1})); System.out.println("Prediction for [1, 1, 0, 0, 1, 1, 1, 0, 0]: " + nn.predict(new double[]{1, 1, 0, 0, 1, 1, 1, 0, 0})); System.out.println("Prediction for [1, 1, 0, 0, 1, 1, 1, 0, 1]: " + nn.predict(new double[]{1, 1, 0, 0, 1, 1, 1, 0, 1})); System.out.println("Prediction for [1, 1, 0, 0, 1, 1, 1, 1, 0]: " + nn.predict(new double[]{1, 1, 0, 0, 1, 1, 1, 1, 0})); System.out.println("Prediction for [1, 1, 0, 0, 1, 1, 1, 1, 1]: " + nn.predict(new double[]{1, 1, 0, 0, 1, 1, 1, 1, 1})); System.out.println("Prediction for [1, 1, 0, 1, 0, 0, 0, 0, 0]: " + nn.predict(new double[]{1, 1, 0, 1, 0, 0, 0, 0, 0})); System.out.println("Prediction for [1, 1, 0, 1, 0, 0, 0, 0, 1]: " + nn.predict(new double[]{1, 1, 0, 1, 0, 0, 0, 0, 1})); System.out.println("Prediction for [1, 1, 0, 1, 0, 0, 0, 1, 0]: " + nn.predict(new double[]{1, 1, 0, 1, 0, 0, 0, 1, 0})); System.out.println("Prediction for [1, 1, 0, 1, 0, 0, 0, 1, 1]: " + nn.predict(new double[]{1, 1, 0, 1, 0, 0, 0, 1, 1})); System.out.println("Prediction for [1, 1, 0, 1, 0, 0, 1, 0, 0]: " + nn.predict(new double[]{1, 1, 0, 1, 0, 0, 1, 0, 0})); System.out.println("Prediction for [1, 1, 0, 1, 0, 0, 1, 0, 1]: " + nn.predict(new double[]{1, 1, 0, 1, 0, 0, 1, 0, 1})); System.out.println("Prediction for [1, 1, 0, 1, 0, 0, 1, 1, 0]: " + nn.predict(new double[]{1, 1, 0, 1, 0, 0, 1, 1, 0})); System.out.println("Prediction for [1, 1, 0, 1, 0, 0, 1, 1, 1]: " + nn.predict(new double[]{1, 1, 0, 1, 0, 0, 1, 1, 1})); System.out.println("Prediction for [1, 1, 0, 1, 0, 1, 0, 0, 0]: " + nn.predict(new double[]{1, 1, 0, 1, 0, 1, 0, 0, 0})); System.out.println("Prediction for [1, 1, 0, 1, 0, 1, 0, 0, 1]: " + nn.predict(new double[]{1, 1, 0, 1, 0, 1, 0, 0, 1})); System.out.println("Prediction for [1, 1, 0, 1, 0, 1, 0, 1, 0]: " + nn.predict(new double[]{1, 1, 0, 1, 0, 1, 0, 1, 0})); System.out.println("Prediction for [1, 1, 0, 1, 0, 1, 0, 1, 1]: " + nn.predict(new double[]{1, 1, 0, 1, 0, 1, 0, 1, 1})); System.out.println("Prediction for [1, 1, 0, 1, 0, 1, 1, 0, 0]: " + nn.predict(new double[]{1, 1, 0, 1, 0, 1, 1, 0, 0})); System.out.println("Prediction for [1, 1, 0, 1, 0, 1, 1, 0, 1]: " + nn.predict(new double[]{1, 1, 0, 1, 0, 1, 1, 0, 1})); System.out.println("Prediction for [1, 1, 0, 1, 0, 1, 1, 1, 0]: " + nn.predict(new double[]{1, 1, 0, 1, 0, 1, 1, 1, 0})); System.out.println("Prediction for [1, 1, 0, 1, 0, 1, 1, 1, 1]: " + nn.predict(new double[]{1, 1, 0, 1, 0, 1, 1, 1, 1})); System.out.println("Prediction for [1, 1, 0, 1, 1, 0, 0, 0, 0]: " + nn.predict(new double[]{1, 1, 0, 1, 1, 0, 0, 0, 0})); System.out.println("Prediction for [1, 1, 0, 1, 1, 0, 0, 0, 1]: " + nn.predict(new double[]{1, 1, 0, 1, 1, 0, 0, 0, 1})); System.out.println("Prediction for [1, 1, 0, 1, 1, 0, 0, 1, 0]: " + nn.predict(new double[]{1, 1, 0, 1, 1, 0, 0, 1, 0})); System.out.println("Prediction for [1, 1, 0, 1, 1, 0, 0, 1, 1]: " + nn.predict(new double[]{1, 1, 0, 1, 1, 0, 0, 1, 1})); System.out.println("Prediction for [1, 1, 0, 1, 1, 0, 1, 0, 0]: " + nn.predict(new double[]{1, 1, 0, 1, 1, 0, 1, 0, 0})); System.out.println("Prediction for [1, 1, 0, 1, 1, 0, 1, 0, 1]: " + nn.predict(new double[]{1, 1, 0, 1, 1, 0, 1, 0, 1})); System.out.println("Prediction for [1, 1, 0, 1, 1, 0, 1, 1, 0]: " + nn.predict(new double[]{1, 1, 0, 1, 1, 0, 1, 1, 0})); System.out.println("Prediction for [1, 1, 0, 1, 1, 0, 1, 1, 1]: " + nn.predict(new double[]{1, 1, 0, 1, 1, 0, 1, 1, 1})); System.out.println("Prediction for [1, 1, 0, 1, 1, 1, 0, 0, 0]: " + nn.predict(new double[]{1, 1, 0, 1, 1, 1, 0, 0, 0})); System.out.println("Prediction for [1, 1, 0, 1, 1, 1, 0, 0, 1]: " + nn.predict(new double[]{1, 1, 0, 1, 1, 1, 0, 0, 1})); System.out.println("Prediction for [1, 1, 0, 1, 1, 1, 0, 1, 0]: " + nn.predict(new double[]{1, 1, 0, 1, 1, 1, 0, 1, 0})); System.out.println("Prediction for [1, 1, 0, 1, 1, 1, 0, 1, 1]: " + nn.predict(new double[]{1, 1, 0, 1, 1, 1, 0, 1, 1})); System.out.println("Prediction for [1, 1, 0, 1, 1, 1, 1, 0, 0]: " + nn.predict(new double[]{1, 1, 0, 1, 1, 1, 1, 0, 0})); System.out.println("Prediction for [1, 1, 0, 1, 1, 1, 1, 0, 1]: " + nn.predict(new double[]{1, 1, 0, 1, 1, 1, 1, 0, 1})); System.out.println("Prediction for [1, 1, 0, 1, 1, 1, 1, 1, 0]: " + nn.predict(new double[]{1, 1, 0, 1, 1, 1, 1, 1, 0})); System.out.println("Prediction for [1, 1, 0, 1, 1, 1, 1, 1, 1]: " + nn.predict(new double[]{1, 1, 0, 1, 1, 1, 1, 1, 1})); System.out.println("Prediction for [1, 1, 1, 0, 0, 0, 0, 0, 0]: " + nn.predict(new double[]{1, 1, 1, 0, 0, 0, 0, 0, 0})); System.out.println("Prediction for [1, 1, 1, 0, 0, 0, 0, 0, 1]: " + nn.predict(new double[]{1, 1, 1, 0, 0, 0, 0, 0, 1})); System.out.println("Prediction for [1, 1, 1, 0, 0, 0, 0, 1, 0]: " + nn.predict(new double[]{1, 1, 1, 0, 0, 0, 0, 1, 0})); System.out.println("Prediction for [1, 1, 1, 0, 0, 0, 0, 1, 1]: " + nn.predict(new double[]{1, 1, 1, 0, 0, 0, 0, 1, 1})); System.out.println("Prediction for [1, 1, 1, 0, 0, 0, 1, 0, 0]: " + nn.predict(new double[]{1, 1, 1, 0, 0, 0, 1, 0, 0})); System.out.println("Prediction for [1, 1, 1, 0, 0, 0, 1, 0, 1]: " + nn.predict(new double[]{1, 1, 1, 0, 0, 0, 1, 0, 1})); System.out.println("Prediction for [1, 1, 1, 0, 0, 0, 1, 1, 0]: " + nn.predict(new double[]{1, 1, 1, 0, 0, 0, 1, 1, 0})); System.out.println("Prediction for [1, 1, 1, 0, 0, 0, 1, 1, 1]: " + nn.predict(new double[]{1, 1, 1, 0, 0, 0, 1, 1, 1})); System.out.println("Prediction for [1, 1, 1, 0, 0, 1, 0, 0, 0]: " + nn.predict(new double[]{1, 1, 1, 0, 0, 1, 0, 0, 0})); System.out.println("Prediction for [1, 1, 1, 0, 0, 1, 0, 0, 1]: " + nn.predict(new double[]{1, 1, 1, 0, 0, 1, 0, 0, 1})); System.out.println("Prediction for [1, 1, 1, 0, 0, 1, 0, 1, 0]: " + nn.predict(new double[]{1, 1, 1, 0, 0, 1, 0, 1, 0})); System.out.println("Prediction for [1, 1, 1, 0, 0, 1, 0, 1, 1]: " + nn.predict(new double[]{1, 1, 1, 0, 0, 1, 0, 1, 1})); System.out.println("Prediction for [1, 1, 1, 0, 0, 1, 1, 0, 0]: " + nn.predict(new double[]{1, 1, 1, 0, 0, 1, 1, 0, 0})); System.out.println("Prediction for [1, 1, 1, 0, 0, 1, 1, 0, 1]: " + nn.predict(new double[]{1, 1, 1, 0, 0, 1, 1, 0, 1})); System.out.println("Prediction for [1, 1, 1, 0, 0, 1, 1, 1, 0]: " + nn.predict(new double[]{1, 1, 1, 0, 0, 1, 1, 1, 0})); System.out.println("Prediction for [1, 1, 1, 0, 0, 1, 1, 1, 1]: " + nn.predict(new double[]{1, 1, 1, 0, 0, 1, 1, 1, 1})); System.out.println("Prediction for [1, 1, 1, 0, 1, 0, 0, 0, 0]: " + nn.predict(new double[]{1, 1, 1, 0, 1, 0, 0, 0, 0})); System.out.println("Prediction for [1, 1, 1, 0, 1, 0, 0, 0, 1]: " + nn.predict(new double[]{1, 1, 1, 0, 1, 0, 0, 0, 1})); System.out.println("Prediction for [1, 1, 1, 0, 1, 0, 0, 1, 0]: " + nn.predict(new double[]{1, 1, 1, 0, 1, 0, 0, 1, 0})); System.out.println("Prediction for [1, 1, 1, 0, 1, 0, 0, 1, 1]: " + nn.predict(new double[]{1, 1, 1, 0, 1, 0, 0, 1, 1})); System.out.println("Prediction for [1, 1, 1, 0, 1, 0, 1, 0, 0]: " + nn.predict(new double[]{1, 1, 1, 0, 1, 0, 1, 0, 0})); System.out.println("Prediction for [1, 1, 1, 0, 1, 0, 1, 0, 1]: " + nn.predict(new double[]{1, 1, 1, 0, 1, 0, 1, 0, 1})); System.out.println("Prediction for [1, 1, 1, 0, 1, 0, 1, 1, 0]: " + nn.predict(new double[]{1, 1, 1, 0, 1, 0, 1, 1, 0})); System.out.println("Prediction for [1, 1, 1, 0, 1, 0, 1, 1, 1]: " + nn.predict(new double[]{1, 1, 1, 0, 1, 0, 1, 1, 1})); System.out.println("Prediction for [1, 1, 1, 0, 1, 1, 0, 0, 0]: " + nn.predict(new double[]{1, 1, 1, 0, 1, 1, 0, 0, 0})); System.out.println("Prediction for [1, 1, 1, 0, 1, 1, 0, 0, 1]: " + nn.predict(new double[]{1, 1, 1, 0, 1, 1, 0, 0, 1})); System.out.println("Prediction for [1, 1, 1, 0, 1, 1, 0, 1, 0]: " + nn.predict(new double[]{1, 1, 1, 0, 1, 1, 0, 1, 0})); System.out.println("Prediction for [1, 1, 1, 0, 1, 1, 0, 1, 1]: " + nn.predict(new double[]{1, 1, 1, 0, 1, 1, 0, 1, 1})); System.out.println("Prediction for [1, 1, 1, 0, 1, 1, 1, 0, 0]: " + nn.predict(new double[]{1, 1, 1, 0, 1, 1, 1, 0, 0})); System.out.println("Prediction for [1, 1, 1, 0, 1, 1, 1, 0, 1]: " + nn.predict(new double[]{1, 1, 1, 0, 1, 1, 1, 0, 1})); System.out.println("Prediction for [1, 1, 1, 0, 1, 1, 1, 1, 0]: " + nn.predict(new double[]{1, 1, 1, 0, 1, 1, 1, 1, 0})); System.out.println("Prediction for [1, 1, 1, 0, 1, 1, 1, 1, 1]: " + nn.predict(new double[]{1, 1, 1, 0, 1, 1, 1, 1, 1})); System.out.println("Prediction for [1, 1, 1, 1, 0, 0, 0, 0, 0]: " + nn.predict(new double[]{1, 1, 1, 1, 0, 0, 0, 0, 0})); System.out.println("Prediction for [1, 1, 1, 1, 0, 0, 0, 0, 1]: " + nn.predict(new double[]{1, 1, 1, 1, 0, 0, 0, 0, 1})); System.out.println("Prediction for [1, 1, 1, 1, 0, 0, 0, 1, 0]: " + nn.predict(new double[]{1, 1, 1, 1, 0, 0, 0, 1, 0})); System.out.println("Prediction for [1, 1, 1, 1, 0, 0, 0, 1, 1]: " + nn.predict(new double[]{1, 1, 1, 1, 0, 0, 0, 1, 1})); System.out.println("Prediction for [1, 1, 1, 1, 0, 0, 1, 0, 0]: " + nn.predict(new double[]{1, 1, 1, 1, 0, 0, 1, 0, 0})); System.out.println("Prediction for [1, 1, 1, 1, 0, 0, 1, 0, 1]: " + nn.predict(new double[]{1, 1, 1, 1, 0, 0, 1, 0, 1})); System.out.println("Prediction for [1, 1, 1, 1, 0, 0, 1, 1, 0]: " + nn.predict(new double[]{1, 1, 1, 1, 0, 0, 1, 1, 0})); System.out.println("Prediction for [1, 1, 1, 1, 0, 0, 1, 1, 1]: " + nn.predict(new double[]{1, 1, 1, 1, 0, 0, 1, 1, 1})); System.out.println("Prediction for [1, 1, 1, 1, 0, 1, 0, 0, 0]: " + nn.predict(new double[]{1, 1, 1, 1, 0, 1, 0, 0, 0})); System.out.println("Prediction for [1, 1, 1, 1, 0, 1, 0, 0, 1]: " + nn.predict(new double[]{1, 1, 1, 1, 0, 1, 0, 0, 1})); System.out.println("Prediction for [1, 1, 1, 1, 0, 1, 0, 1, 0]: " + nn.predict(new double[]{1, 1, 1, 1, 0, 1, 0, 1, 0})); System.out.println("Prediction for [1, 1, 1, 1, 0, 1, 0, 1, 1]: " + nn.predict(new double[]{1, 1, 1, 1, 0, 1, 0, 1, 1})); System.out.println("Prediction for [1, 1, 1, 1, 0, 1, 1, 0, 0]: " + nn.predict(new double[]{1, 1, 1, 1, 0, 1, 1, 0, 0})); System.out.println("Prediction for [1, 1, 1, 1, 0, 1, 1, 0, 1]: " + nn.predict(new double[]{1, 1, 1, 1, 0, 1, 1, 0, 1})); System.out.println("Prediction for [1, 1, 1, 1, 0, 1, 1, 1, 0]: " + nn.predict(new double[]{1, 1, 1, 1, 0, 1, 1, 1, 0})); System.out.println("Prediction for [1, 1, 1, 1, 0, 1, 1, 1, 1]: " + nn.predict(new double[]{1, 1, 1, 1, 0, 1, 1, 1, 1})); System.out.println("Prediction for [1, 1, 1, 1, 1, 0, 0, 0, 0]: " + nn.predict(new double[]{1, 1, 1, 1, 1, 0, 0, 0, 0})); System.out.println("Prediction for [1, 1, 1, 1, 1, 0, 0, 0, 1]: " + nn.predict(new double[]{1, 1, 1, 1, 1, 0, 0, 0, 1})); System.out.println("Prediction for [1, 1, 1, 1, 1, 0, 0, 1, 0]: " + nn.predict(new double[]{1, 1, 1, 1, 1, 0, 0, 1, 0})); System.out.println("Prediction for [1, 1, 1, 1, 1, 0, 0, 1, 1]: " + nn.predict(new double[]{1, 1, 1, 1, 1, 0, 0, 1, 1})); System.out.println("Prediction for [1, 1, 1, 1, 1, 0, 1, 0, 0]: " + nn.predict(new double[]{1, 1, 1, 1, 1, 0, 1, 0, 0})); System.out.println("Prediction for [1, 1, 1, 1, 1, 0, 1, 0, 1]: " + nn.predict(new double[]{1, 1, 1, 1, 1, 0, 1, 0, 1})); System.out.println("Prediction for [1, 1, 1, 1, 1, 0, 1, 1, 0]: " + nn.predict(new double[]{1, 1, 1, 1, 1, 0, 1, 1, 0})); System.out.println("Prediction for [1, 1, 1, 1, 1, 0, 1, 1, 1]: " + nn.predict(new double[]{1, 1, 1, 1, 1, 0, 1, 1, 1})); System.out.println("Prediction for [1, 1, 1, 1, 1, 1, 0, 0, 0]: " + nn.predict(new double[]{1, 1, 1, 1, 1, 1, 0, 0, 0})); System.out.println("Prediction for [1, 1, 1, 1, 1, 1, 0, 0, 1]: " + nn.predict(new double[]{1, 1, 1, 1, 1, 1, 0, 0, 1})); System.out.println("Prediction for [1, 1, 1, 1, 1, 1, 0, 1, 0]: " + nn.predict(new double[]{1, 1, 1, 1, 1, 1, 0, 1, 0})); System.out.println("Prediction for [1, 1, 1, 1, 1, 1, 0, 1, 1]: " + nn.predict(new double[]{1, 1, 1, 1, 1, 1, 0, 1, 1})); System.out.println("Prediction for [1, 1, 1, 1, 1, 1, 1, 0, 0]: " + nn.predict(new double[]{1, 1, 1, 1, 1, 1, 1, 0, 0})); System.out.println("Prediction for [1, 1, 1, 1, 1, 1, 1, 0, 1]: " + nn.predict(new double[]{1, 1, 1, 1, 1, 1, 1, 0, 1})); System.out.println("Prediction for [1, 1, 1, 1, 1, 1, 1, 1, 0]: " + nn.predict(new double[]{1, 1, 1, 1, 1, 1, 1, 1, 0})); System.out.println("Prediction for [1, 1, 1, 1, 1, 1, 1, 1, 1]: " + nn.predict(new double[]{1, 1, 1, 1, 1, 1, 1, 1, 1})); } } run: Epoch 2000, Error: 52.451551882360036 Epoch 4000, Error: 31.707144021981634 Epoch 6000, Error: 16.8717906992642 Epoch 8000, Error: 11.580722094331293 Epoch 10000, Error: 8.481827590063295 Epoch 12000, Error: 6.956125519486862 Epoch 14000, Error: 5.568760773703237 Epoch 16000, Error: 4.493248237614515 Epoch 18000, Error: 3.7103603783767722 Epoch 20000, Error: 3.2636811254227696 Epoch 22000, Error: 2.7855791672626737 Epoch 24000, Error: 2.3907075512281533 Epoch 26000, Error: 2.103757600728982 Epoch 28000, Error: 1.8203912755088996 Epoch 30000, Error: 1.6460082295246317 Epoch 32000, Error: 1.4841126968404992 Epoch 34000, Error: 1.3425065139755252 Epoch 36000, Error: 1.238685963743492 Epoch 38000, Error: 1.1614882249300917 Epoch 40000, Error: 1.1055794269285453 Epoch 42000, Error: 1.0609986005185013 Epoch 44000, Error: 1.010127928687235 Epoch 46000, Error: 0.9767334629057545 Epoch 48000, Error: 0.944380151468777 Epoch 50000, Error: 0.9168364797299632 Epoch 52000, Error: 0.8871847496247405 Epoch 54000, Error: 0.8674593415148122 Epoch 56000, Error: 0.8517135803358193 Epoch 58000, Error: 0.8274156019736346 Epoch 60000, Error: 0.8077891758568904 Epoch 62000, Error: 0.7903260271817737 Epoch 64000, Error: 0.7738944754375546 Epoch 66000, Error: 0.7596446130912603 Epoch 68000, Error: 0.7455503467843242 Epoch 70000, Error: 0.733113053729717 Epoch 72000, Error: 0.7216830384255954 Epoch 74000, Error: 0.7107172209302016 Epoch 76000, Error: 0.6999204977286727 Epoch 78000, Error: 0.6909253442159263 Epoch 80000, Error: 0.6779540581815748 Epoch 82000, Error: 0.6729191214068203 Epoch 84000, Error: 0.6647472478558226 Epoch 86000, Error: 0.6545041538259536 Epoch 88000, Error: 0.6485849487137458 Epoch 90000, Error: 0.6409668625457688 Epoch 92000, Error: 0.6338876210454332 Epoch 94000, Error: 0.6271993960133858 Epoch 96000, Error: 0.6200443392722925 Epoch 98000, Error: 0.6131641962113463 Epoch 100000, Error: 0.6055875978978504 Prediction for [0, 0, 0, 0, 0, 0, 0, 0, 0]: 0.0 Prediction for [0, 0, 0, 0, 0, 0, 0, 0, 1]: 1.0029322924298496 Prediction for [0, 0, 0, 0, 0, 0, 0, 1, 0]: 0.0 Prediction for [0, 0, 0, 0, 0, 0, 0, 1, 1]: 0.0 Prediction for [0, 0, 0, 0, 0, 0, 1, 0, 0]: 0.0 Prediction for [0, 0, 0, 0, 0, 0, 1, 0, 1]: 1.0001584132525174 Prediction for [0, 0, 0, 0, 0, 0, 1, 1, 0]: 0.0 Prediction for [0, 0, 0, 0, 0, 0, 1, 1, 1]: 1.002008788417899 Prediction for [0, 0, 0, 0, 0, 1, 0, 0, 0]: 0.0 Prediction for [0, 0, 0, 0, 0, 1, 0, 0, 1]: 0.0 Prediction for [0, 0, 0, 0, 0, 1, 0, 1, 0]: 0.0 Prediction for [0, 0, 0, 0, 0, 1, 0, 1, 1]: 1.0007155017702454 Prediction for [0, 0, 0, 0, 0, 1, 1, 0, 0]: 0.0 Prediction for [0, 0, 0, 0, 0, 1, 1, 0, 1]: 1.0037306797702428 Prediction for [0, 0, 0, 0, 0, 1, 1, 1, 0]: 0.0 Prediction for [0, 0, 0, 0, 0, 1, 1, 1, 1]: 0.0 Prediction for [0, 0, 0, 0, 1, 0, 0, 0, 0]: 0.0 Prediction for [0, 0, 0, 0, 1, 0, 0, 0, 1]: 1.0082046849989963 Prediction for [0, 0, 0, 0, 1, 0, 0, 1, 0]: 0.0 Prediction for [0, 0, 0, 0, 1, 0, 0, 1, 1]: 1.000963020031036 Prediction for [0, 0, 0, 0, 1, 0, 1, 0, 0]: 0.0 Prediction for [0, 0, 0, 0, 1, 0, 1, 0, 1]: 0.0 Prediction for [0, 0, 0, 0, 1, 0, 1, 1, 0]: 0.0 Prediction for [0, 0, 0, 0, 1, 0, 1, 1, 1]: 1.000951902224271 Prediction for [0, 0, 0, 0, 1, 1, 0, 0, 0]: 0.0 Prediction for [0, 0, 0, 0, 1, 1, 0, 0, 1]: 0.005561024998525177 Prediction for [0, 0, 0, 0, 1, 1, 0, 1, 0]: 0.0 Prediction for [0, 0, 0, 0, 1, 1, 0, 1, 1]: 0.0 Prediction for [0, 0, 0, 0, 1, 1, 1, 0, 0]: 0.0 Prediction for [0, 0, 0, 0, 1, 1, 1, 0, 1]: 1.0032833984102814 Prediction for [0, 0, 0, 0, 1, 1, 1, 1, 0]: 0.0 Prediction for [0, 0, 0, 0, 1, 1, 1, 1, 1]: 0.9998506288613376 Prediction for [0, 0, 0, 1, 0, 0, 0, 0, 0]: 0.0 Prediction for [0, 0, 0, 1, 0, 0, 0, 0, 1]: 0.0 Prediction for [0, 0, 0, 1, 0, 0, 0, 1, 0]: 0.0 Prediction for [0, 0, 0, 1, 0, 0, 0, 1, 1]: 0.0 Prediction for [0, 0, 0, 1, 0, 0, 1, 0, 0]: 0.0 Prediction for [0, 0, 0, 1, 0, 0, 1, 0, 1]: 0.9969347909902329 Prediction for [0, 0, 0, 1, 0, 0, 1, 1, 0]: 0.0 Prediction for [0, 0, 0, 1, 0, 0, 1, 1, 1]: 0.0 Prediction for [0, 0, 0, 1, 0, 1, 0, 0, 0]: 0.0 Prediction for [0, 0, 0, 1, 0, 1, 0, 0, 1]: 1.0002154142574202 Prediction for [0, 0, 0, 1, 0, 1, 0, 1, 0]: 0.0 Prediction for [0, 0, 0, 1, 0, 1, 0, 1, 1]: 1.0030008166588216 Prediction for [0, 0, 0, 1, 0, 1, 1, 0, 0]: 0.0 Prediction for [0, 0, 0, 1, 0, 1, 1, 0, 1]: 0.0 Prediction for [0, 0, 0, 1, 0, 1, 1, 1, 0]: 0.0 Prediction for [0, 0, 0, 1, 0, 1, 1, 1, 1]: 0.9996787139196419 Prediction for [0, 0, 0, 1, 1, 0, 0, 0, 0]: 0.0 Prediction for [0, 0, 0, 1, 1, 0, 0, 0, 1]: 0.0 Prediction for [0, 0, 0, 1, 1, 0, 0, 1, 0]: 0.0 Prediction for [0, 0, 0, 1, 1, 0, 0, 1, 1]: 0.0 Prediction for [0, 0, 0, 1, 1, 0, 1, 0, 0]: 0.0 Prediction for [0, 0, 0, 1, 1, 0, 1, 0, 1]: 0.995948835587976 Prediction for [0, 0, 0, 1, 1, 0, 1, 1, 0]: 0.0 Prediction for [0, 0, 0, 1, 1, 0, 1, 1, 1]: 0.0158368874968855 Prediction for [0, 0, 0, 1, 1, 1, 0, 0, 0]: 0.0 Prediction for [0, 0, 0, 1, 1, 1, 0, 0, 1]: 0.0 Prediction for [0, 0, 0, 1, 1, 1, 0, 1, 0]: 0.0 Prediction for [0, 0, 0, 1, 1, 1, 0, 1, 1]: 1.0024567019333235 Prediction for [0, 0, 0, 1, 1, 1, 1, 0, 0]: 0.0 Prediction for [0, 0, 0, 1, 1, 1, 1, 0, 1]: 0.9971564442587857 Prediction for [0, 0, 0, 1, 1, 1, 1, 1, 0]: 0.0 Prediction for [0, 0, 0, 1, 1, 1, 1, 1, 1]: 2.3147283027302734E-4 Prediction for [0, 0, 1, 0, 0, 0, 0, 0, 0]: 0.0 Prediction for [0, 0, 1, 0, 0, 0, 0, 0, 1]: 0.003074418341085572 Prediction for [0, 0, 1, 0, 0, 0, 0, 1, 0]: 0.0 Prediction for [0, 0, 1, 0, 0, 0, 0, 1, 1]: 0.9973577943526859 Prediction for [0, 0, 1, 0, 0, 0, 1, 0, 0]: 0.0 Prediction for [0, 0, 1, 0, 0, 0, 1, 0, 1]: 0.0 Prediction for [0, 0, 1, 0, 0, 0, 1, 1, 0]: 0.0 Prediction for [0, 0, 1, 0, 0, 0, 1, 1, 1]: 0.9991616724279542 Prediction for [0, 0, 1, 0, 0, 1, 0, 0, 0]: 0.0 Prediction for [0, 0, 1, 0, 0, 1, 0, 0, 1]: 1.005528364690135 Prediction for [0, 0, 1, 0, 0, 1, 0, 1, 0]: 0.0 Prediction for [0, 0, 1, 0, 0, 1, 0, 1, 1]: 0.0 Prediction for [0, 0, 1, 0, 0, 1, 1, 0, 0]: 0.0 Prediction for [0, 0, 1, 0, 0, 1, 1, 0, 1]: 0.0 Prediction for [0, 0, 1, 0, 0, 1, 1, 1, 0]: 0.0 Prediction for [0, 0, 1, 0, 0, 1, 1, 1, 1]: 1.0004561835061123 Prediction for [0, 0, 1, 0, 1, 0, 0, 0, 0]: 0.0 Prediction for [0, 0, 1, 0, 1, 0, 0, 0, 1]: 0.0 Prediction for [0, 0, 1, 0, 1, 0, 0, 1, 0]: 0.0 Prediction for [0, 0, 1, 0, 1, 0, 0, 1, 1]: 0.9987012057436155 Prediction for [0, 0, 1, 0, 1, 0, 1, 0, 0]: 0.0 Prediction for [0, 0, 1, 0, 1, 0, 1, 0, 1]: 0.0 Prediction for [0, 0, 1, 0, 1, 0, 1, 1, 0]: 0.0 Prediction for [0, 0, 1, 0, 1, 0, 1, 1, 1]: 0.0 Prediction for [0, 0, 1, 0, 1, 1, 0, 0, 0]: 0.0 Prediction for [0, 0, 1, 0, 1, 1, 0, 0, 1]: 0.9984621571718089 Prediction for [0, 0, 1, 0, 1, 1, 0, 1, 0]: 0.0 Prediction for [0, 0, 1, 0, 1, 1, 0, 1, 1]: 0.0 Prediction for [0, 0, 1, 0, 1, 1, 1, 0, 0]: 0.0 Prediction for [0, 0, 1, 0, 1, 1, 1, 0, 1]: 0.0 Prediction for [0, 0, 1, 0, 1, 1, 1, 1, 0]: 0.0 Prediction for [0, 0, 1, 0, 1, 1, 1, 1, 1]: 0.0011346559539746615 Prediction for [0, 0, 1, 1, 0, 0, 0, 0, 0]: 0.0 Prediction for [0, 0, 1, 1, 0, 0, 0, 0, 1]: 0.9954658664640776 Prediction for [0, 0, 1, 1, 0, 0, 0, 1, 0]: 0.0 Prediction for [0, 0, 1, 1, 0, 0, 0, 1, 1]: 0.0 Prediction for [0, 0, 1, 1, 0, 0, 1, 0, 0]: 0.0 Prediction for [0, 0, 1, 1, 0, 0, 1, 0, 1]: 0.9987444506721506 Prediction for [0, 0, 1, 1, 0, 0, 1, 1, 0]: 0.0 Prediction for [0, 0, 1, 1, 0, 0, 1, 1, 1]: 1.0032651415297291 Prediction for [0, 0, 1, 1, 0, 1, 0, 0, 0]: 0.0 Prediction for [0, 0, 1, 1, 0, 1, 0, 0, 1]: 0.0 Prediction for [0, 0, 1, 1, 0, 1, 0, 1, 0]: 0.0 Prediction for [0, 0, 1, 1, 0, 1, 0, 1, 1]: 1.0009779538084969 Prediction for [0, 0, 1, 1, 0, 1, 1, 0, 0]: 0.0 Prediction for [0, 0, 1, 1, 0, 1, 1, 0, 1]: 0.9950502153396128 Prediction for [0, 0, 1, 1, 0, 1, 1, 1, 0]: 0.0 Prediction for [0, 0, 1, 1, 0, 1, 1, 1, 1]: 0.0 Prediction for [0, 0, 1, 1, 1, 0, 0, 0, 0]: 0.0 Prediction for [0, 0, 1, 1, 1, 0, 0, 0, 1]: 1.0072640440983252 Prediction for [0, 0, 1, 1, 1, 0, 0, 1, 0]: 0.0 Prediction for [0, 0, 1, 1, 1, 0, 0, 1, 1]: 0.0 Prediction for [0, 0, 1, 1, 1, 0, 1, 0, 0]: 0.0 Prediction for [0, 0, 1, 1, 1, 0, 1, 0, 1]: 0.0 Prediction for [0, 0, 1, 1, 1, 0, 1, 1, 0]: 0.0 Prediction for [0, 0, 1, 1, 1, 0, 1, 1, 1]: 0.0 Prediction for [0, 0, 1, 1, 1, 1, 0, 0, 0]: 0.0 Prediction for [0, 0, 1, 1, 1, 1, 0, 0, 1]: 0.0024867453421006935 Prediction for [0, 0, 1, 1, 1, 1, 0, 1, 0]: 0.0 Prediction for [0, 0, 1, 1, 1, 1, 0, 1, 1]: 0.0 Prediction for [0, 0, 1, 1, 1, 1, 1, 0, 0]: 0.0 Prediction for [0, 0, 1, 1, 1, 1, 1, 0, 1]: 0.003951581166587115 Prediction for [0, 0, 1, 1, 1, 1, 1, 1, 0]: 0.0 Prediction for [0, 0, 1, 1, 1, 1, 1, 1, 1]: 1.0099197376094073 Prediction for [0, 1, 0, 0, 0, 0, 0, 0, 0]: 0.0 Prediction for [0, 1, 0, 0, 0, 0, 0, 0, 1]: 0.0 Prediction for [0, 1, 0, 0, 0, 0, 0, 1, 0]: 0.0 Prediction for [0, 1, 0, 0, 0, 0, 0, 1, 1]: 1.0003574604694494 Prediction for [0, 1, 0, 0, 0, 0, 1, 0, 0]: 0.0 Prediction for [0, 1, 0, 0, 0, 0, 1, 0, 1]: 0.008034098569987602 Prediction for [0, 1, 0, 0, 0, 0, 1, 1, 0]: 0.0 Prediction for [0, 1, 0, 0, 0, 0, 1, 1, 1]: 0.0 Prediction for [0, 1, 0, 0, 0, 1, 0, 0, 0]: 0.0 Prediction for [0, 1, 0, 0, 0, 1, 0, 0, 1]: 1.003767365944774 Prediction for [0, 1, 0, 0, 0, 1, 0, 1, 0]: 0.0 Prediction for [0, 1, 0, 0, 0, 1, 0, 1, 1]: 1.0004039877691122 Prediction for [0, 1, 0, 0, 0, 1, 1, 0, 0]: 0.0 Prediction for [0, 1, 0, 0, 0, 1, 1, 0, 1]: 0.0 Prediction for [0, 1, 0, 0, 0, 1, 1, 1, 0]: 0.0 Prediction for [0, 1, 0, 0, 0, 1, 1, 1, 1]: 0.002685637474658442 Prediction for [0, 1, 0, 0, 1, 0, 0, 0, 0]: 0.0 Prediction for [0, 1, 0, 0, 1, 0, 0, 0, 1]: 0.040853334077697756 Prediction for [0, 1, 0, 0, 1, 0, 0, 1, 0]: 0.0 Prediction for [0, 1, 0, 0, 1, 0, 0, 1, 1]: 0.0 Prediction for [0, 1, 0, 0, 1, 0, 1, 0, 0]: 0.0 Prediction for [0, 1, 0, 0, 1, 0, 1, 0, 1]: 1.0119659306907662 Prediction for [0, 1, 0, 0, 1, 0, 1, 1, 0]: 0.0 Prediction for [0, 1, 0, 0, 1, 0, 1, 1, 1]: 1.0088770661412285 Prediction for [0, 1, 0, 0, 1, 1, 0, 0, 0]: 0.0 Prediction for [0, 1, 0, 0, 1, 1, 0, 0, 1]: 0.0 Prediction for [0, 1, 0, 0, 1, 1, 0, 1, 0]: 0.0 Prediction for [0, 1, 0, 0, 1, 1, 0, 1, 1]: 0.0 Prediction for [0, 1, 0, 0, 1, 1, 1, 0, 0]: 0.0 Prediction for [0, 1, 0, 0, 1, 1, 1, 0, 1]: 1.0078258598722476 Prediction for [0, 1, 0, 0, 1, 1, 1, 1, 0]: 0.0 Prediction for [0, 1, 0, 0, 1, 1, 1, 1, 1]: 0.0 Prediction for [0, 1, 0, 1, 0, 0, 0, 0, 0]: 0.0 Prediction for [0, 1, 0, 1, 0, 0, 0, 0, 1]: 0.010865775047043336 Prediction for [0, 1, 0, 1, 0, 0, 0, 1, 0]: 0.0 Prediction for [0, 1, 0, 1, 0, 0, 0, 1, 1]: 1.0026820538452599 Prediction for [0, 1, 0, 1, 0, 0, 1, 0, 0]: 0.0 Prediction for [0, 1, 0, 1, 0, 0, 1, 0, 1]: 0.0 Prediction for [0, 1, 0, 1, 0, 0, 1, 1, 0]: 0.0 Prediction for [0, 1, 0, 1, 0, 0, 1, 1, 1]: 1.0103824777788928 Prediction for [0, 1, 0, 1, 0, 1, 0, 0, 0]: 0.0 Prediction for [0, 1, 0, 1, 0, 1, 0, 0, 1]: 0.008447198771444953 Prediction for [0, 1, 0, 1, 0, 1, 0, 1, 0]: 0.0 Prediction for [0, 1, 0, 1, 0, 1, 0, 1, 1]: 0.0 Prediction for [0, 1, 0, 1, 0, 1, 1, 0, 0]: 0.0 Prediction for [0, 1, 0, 1, 0, 1, 1, 0, 1]: 1.0106172905539639 Prediction for [0, 1, 0, 1, 0, 1, 1, 1, 0]: 0.0 Prediction for [0, 1, 0, 1, 0, 1, 1, 1, 1]: 0.016426590280938846 Prediction for [0, 1, 0, 1, 1, 0, 0, 0, 0]: 0.0 Prediction for [0, 1, 0, 1, 1, 0, 0, 0, 1]: 0.0 Prediction for [0, 1, 0, 1, 1, 0, 0, 1, 0]: 0.0 Prediction for [0, 1, 0, 1, 1, 0, 0, 1, 1]: 1.0147024963749471 Prediction for [0, 1, 0, 1, 1, 0, 1, 0, 0]: 0.0 Prediction for [0, 1, 0, 1, 1, 0, 1, 0, 1]: 0.981471700164998 Prediction for [0, 1, 0, 1, 1, 0, 1, 1, 0]: 0.0 Prediction for [0, 1, 0, 1, 1, 0, 1, 1, 1]: 0.0 Prediction for [0, 1, 0, 1, 1, 1, 0, 0, 0]: 0.0 Prediction for [0, 1, 0, 1, 1, 1, 0, 0, 1]: 0.0 Prediction for [0, 1, 0, 1, 1, 1, 0, 1, 0]: 0.0 Prediction for [0, 1, 0, 1, 1, 1, 0, 1, 1]: 0.006292934771463088 Prediction for [0, 1, 0, 1, 1, 1, 1, 0, 0]: 0.0 Prediction for [0, 1, 0, 1, 1, 1, 1, 0, 1]: 0.0 Prediction for [0, 1, 0, 1, 1, 1, 1, 1, 0]: 0.0 Prediction for [0, 1, 0, 1, 1, 1, 1, 1, 1]: 1.0010245701603866 Prediction for [0, 1, 1, 0, 0, 0, 0, 0, 0]: 0.0 Prediction for [0, 1, 1, 0, 0, 0, 0, 0, 1]: 0.9852238389874755 Prediction for [0, 1, 1, 0, 0, 0, 0, 1, 0]: 0.0 Prediction for [0, 1, 1, 0, 0, 0, 0, 1, 1]: 0.0 Prediction for [0, 1, 1, 0, 0, 0, 1, 0, 0]: 0.0 Prediction for [0, 1, 1, 0, 0, 0, 1, 0, 1]: 0.9884693909925657 Prediction for [0, 1, 1, 0, 0, 0, 1, 1, 0]: 0.0 Prediction for [0, 1, 1, 0, 0, 0, 1, 1, 1]: 0.9908295627355495 Prediction for [0, 1, 1, 0, 0, 1, 0, 0, 0]: 0.0 Prediction for [0, 1, 1, 0, 0, 1, 0, 0, 1]: 0.0 Prediction for [0, 1, 1, 0, 0, 1, 0, 1, 0]: 0.0 Prediction for [0, 1, 1, 0, 0, 1, 0, 1, 1]: 0.0 Prediction for [0, 1, 1, 0, 0, 1, 1, 0, 0]: 0.0 Prediction for [0, 1, 1, 0, 0, 1, 1, 0, 1]: 0.0 Prediction for [0, 1, 1, 0, 0, 1, 1, 1, 0]: 0.0 Prediction for [0, 1, 1, 0, 0, 1, 1, 1, 1]: 0.0 Prediction for [0, 1, 1, 0, 1, 0, 0, 0, 0]: 0.0 Prediction for [0, 1, 1, 0, 1, 0, 0, 0, 1]: 0.0 Prediction for [0, 1, 1, 0, 1, 0, 0, 1, 0]: 0.0 Prediction for [0, 1, 1, 0, 1, 0, 0, 1, 1]: 0.9717382559173222 Prediction for [0, 1, 1, 0, 1, 0, 1, 0, 0]: 0.0 Prediction for [0, 1, 1, 0, 1, 0, 1, 0, 1]: 0.0 Prediction for [0, 1, 1, 0, 1, 0, 1, 1, 0]: 0.0 Prediction for [0, 1, 1, 0, 1, 0, 1, 1, 1]: 0.0 Prediction for [0, 1, 1, 0, 1, 1, 0, 0, 0]: 0.0 Prediction for [0, 1, 1, 0, 1, 1, 0, 0, 1]: 0.0 Prediction for [0, 1, 1, 0, 1, 1, 0, 1, 0]: 0.0 Prediction for [0, 1, 1, 0, 1, 1, 0, 1, 1]: 0.0 Prediction for [0, 1, 1, 0, 1, 1, 1, 0, 0]: 0.0 Prediction for [0, 1, 1, 0, 1, 1, 1, 0, 1]: 0.0 Prediction for [0, 1, 1, 0, 1, 1, 1, 1, 0]: 0.0 Prediction for [0, 1, 1, 0, 1, 1, 1, 1, 1]: 0.9882074199299513 Prediction for [0, 1, 1, 1, 0, 0, 0, 0, 0]: 0.0 Prediction for [0, 1, 1, 1, 0, 0, 0, 0, 1]: 0.0 Prediction for [0, 1, 1, 1, 0, 0, 0, 1, 0]: 0.0 Prediction for [0, 1, 1, 1, 0, 0, 0, 1, 1]: 1.0009047154183124 Prediction for [0, 1, 1, 1, 0, 0, 1, 0, 0]: 0.0 Prediction for [0, 1, 1, 1, 0, 0, 1, 0, 1]: 1.0060251513369316 Prediction for [0, 1, 1, 1, 0, 0, 1, 1, 0]: 0.0 Prediction for [0, 1, 1, 1, 0, 0, 1, 1, 1]: 0.0 Prediction for [0, 1, 1, 1, 0, 1, 0, 0, 0]: 0.0 Prediction for [0, 1, 1, 1, 0, 1, 0, 0, 1]: 0.9992772409937345 Prediction for [0, 1, 1, 1, 0, 1, 0, 1, 0]: 0.0 Prediction for [0, 1, 1, 1, 0, 1, 0, 1, 1]: 0.0 Prediction for [0, 1, 1, 1, 0, 1, 1, 0, 0]: 0.0 Prediction for [0, 1, 1, 1, 0, 1, 1, 0, 1]: 0.0 Prediction for [0, 1, 1, 1, 0, 1, 1, 1, 0]: 0.0 Prediction for [0, 1, 1, 1, 0, 1, 1, 1, 1]: 0.9940313730861083 Prediction for [0, 1, 1, 1, 1, 0, 0, 0, 0]: 0.0 Prediction for [0, 1, 1, 1, 1, 0, 0, 0, 1]: 0.6114210701473386 Prediction for [0, 1, 1, 1, 1, 0, 0, 1, 0]: 0.0 Prediction for [0, 1, 1, 1, 1, 0, 0, 1, 1]: 0.0 Prediction for [0, 1, 1, 1, 1, 0, 1, 0, 0]: 0.0 Prediction for [0, 1, 1, 1, 1, 0, 1, 0, 1]: 0.0 Prediction for [0, 1, 1, 1, 1, 0, 1, 1, 0]: 0.0 Prediction for [0, 1, 1, 1, 1, 0, 1, 1, 1]: 0.18617672247726214 Prediction for [0, 1, 1, 1, 1, 1, 0, 0, 0]: 0.0 Prediction for [0, 1, 1, 1, 1, 1, 0, 0, 1]: 0.0 Prediction for [0, 1, 1, 1, 1, 1, 0, 1, 0]: 0.0 Prediction for [0, 1, 1, 1, 1, 1, 0, 1, 1]: 1.009648230629593 Prediction for [0, 1, 1, 1, 1, 1, 1, 0, 0]: 0.0 Prediction for [0, 1, 1, 1, 1, 1, 1, 0, 1]: 0.0 Prediction for [0, 1, 1, 1, 1, 1, 1, 1, 0]: 0.0 Prediction for [0, 1, 1, 1, 1, 1, 1, 1, 1]: 0.0 Prediction for [1, 0, 0, 0, 0, 0, 0, 0, 0]: 0.0 Prediction for [1, 0, 0, 0, 0, 0, 0, 0, 1]: 0.9903749254970613 Prediction for [1, 0, 0, 0, 0, 0, 0, 1, 0]: 0.0 Prediction for [1, 0, 0, 0, 0, 0, 0, 1, 1]: 0.0 Prediction for [1, 0, 0, 0, 0, 0, 1, 0, 0]: 0.0 Prediction for [1, 0, 0, 0, 0, 0, 1, 0, 1]: 0.003299527614217812 Prediction for [1, 0, 0, 0, 0, 0, 1, 1, 0]: 0.0 Prediction for [1, 0, 0, 0, 0, 0, 1, 1, 1]: 0.9944588157043315 Prediction for [1, 0, 0, 0, 0, 1, 0, 0, 0]: 0.0 Prediction for [1, 0, 0, 0, 0, 1, 0, 0, 1]: 0.0 Prediction for [1, 0, 0, 0, 0, 1, 0, 1, 0]: 0.0 Prediction for [1, 0, 0, 0, 0, 1, 0, 1, 1]: 0.0 Prediction for [1, 0, 0, 0, 0, 1, 1, 0, 0]: 0.0 Prediction for [1, 0, 0, 0, 0, 1, 1, 0, 1]: 1.0038817245799683 Prediction for [1, 0, 0, 0, 0, 1, 1, 1, 0]: 0.0 Prediction for [1, 0, 0, 0, 0, 1, 1, 1, 1]: 1.0097622139159244 Prediction for [1, 0, 0, 0, 1, 0, 0, 0, 0]: 0.0 Prediction for [1, 0, 0, 0, 1, 0, 0, 0, 1]: 0.001327405061337661 Prediction for [1, 0, 0, 0, 1, 0, 0, 1, 0]: 0.0 Prediction for [1, 0, 0, 0, 1, 0, 0, 1, 1]: 0.0 Prediction for [1, 0, 0, 0, 1, 0, 1, 0, 0]: 0.0 Prediction for [1, 0, 0, 0, 1, 0, 1, 0, 1]: 1.0034214532504366 Prediction for [1, 0, 0, 0, 1, 0, 1, 1, 0]: 0.0 Prediction for [1, 0, 0, 0, 1, 0, 1, 1, 1]: 0.0 Prediction for [1, 0, 0, 0, 1, 1, 0, 0, 0]: 0.0 Prediction for [1, 0, 0, 0, 1, 1, 0, 0, 1]: 1.0019759765421536 Prediction for [1, 0, 0, 0, 1, 1, 0, 1, 0]: 0.0 Prediction for [1, 0, 0, 0, 1, 1, 0, 1, 1]: 1.0026692260329328 Prediction for [1, 0, 0, 0, 1, 1, 1, 0, 0]: 0.0 Prediction for [1, 0, 0, 0, 1, 1, 1, 0, 1]: 0.0 Prediction for [1, 0, 0, 0, 1, 1, 1, 1, 0]: 0.0 Prediction for [1, 0, 0, 0, 1, 1, 1, 1, 1]: 0.0 Prediction for [1, 0, 0, 1, 0, 0, 0, 0, 0]: 0.0 Prediction for [1, 0, 0, 1, 0, 0, 0, 0, 1]: 0.0 Prediction for [1, 0, 0, 1, 0, 0, 0, 1, 0]: 0.0 Prediction for [1, 0, 0, 1, 0, 0, 0, 1, 1]: 0.0 Prediction for [1, 0, 0, 1, 0, 0, 1, 0, 0]: 0.0 Prediction for [1, 0, 0, 1, 0, 0, 1, 0, 1]: 0.9913182367838012 Prediction for [1, 0, 0, 1, 0, 0, 1, 1, 0]: 0.0 Prediction for [1, 0, 0, 1, 0, 0, 1, 1, 1]: 0.0 Prediction for [1, 0, 0, 1, 0, 1, 0, 0, 0]: 0.0 Prediction for [1, 0, 0, 1, 0, 1, 0, 0, 1]: 0.0 Prediction for [1, 0, 0, 1, 0, 1, 0, 1, 0]: 0.0 Prediction for [1, 0, 0, 1, 0, 1, 0, 1, 1]: 0.0 Prediction for [1, 0, 0, 1, 0, 1, 1, 0, 0]: 0.0 Prediction for [1, 0, 0, 1, 0, 1, 1, 0, 1]: 0.0 Prediction for [1, 0, 0, 1, 0, 1, 1, 1, 0]: 0.0 Prediction for [1, 0, 0, 1, 0, 1, 1, 1, 1]: 0.0 Prediction for [1, 0, 0, 1, 1, 0, 0, 0, 0]: 0.0 Prediction for [1, 0, 0, 1, 1, 0, 0, 0, 1]: 0.0 Prediction for [1, 0, 0, 1, 1, 0, 0, 1, 0]: 0.0 Prediction for [1, 0, 0, 1, 1, 0, 0, 1, 1]: 0.9884657828164292 Prediction for [1, 0, 0, 1, 1, 0, 1, 0, 0]: 0.0 Prediction for [1, 0, 0, 1, 1, 0, 1, 0, 1]: 0.0 Prediction for [1, 0, 0, 1, 1, 0, 1, 1, 0]: 0.0 Prediction for [1, 0, 0, 1, 1, 0, 1, 1, 1]: 1.007706869050522 Prediction for [1, 0, 0, 1, 1, 1, 0, 0, 0]: 0.0 Prediction for [1, 0, 0, 1, 1, 1, 0, 0, 1]: 0.9905506184428328 Prediction for [1, 0, 0, 1, 1, 1, 0, 1, 0]: 0.0 Prediction for [1, 0, 0, 1, 1, 1, 0, 1, 1]: 0.0 Prediction for [1, 0, 0, 1, 1, 1, 1, 0, 0]: 0.0 Prediction for [1, 0, 0, 1, 1, 1, 1, 0, 1]: 0.9908097283399391 Prediction for [1, 0, 0, 1, 1, 1, 1, 1, 0]: 0.0 Prediction for [1, 0, 0, 1, 1, 1, 1, 1, 1]: 0.018700973863153614 Prediction for [1, 0, 1, 0, 0, 0, 0, 0, 0]: 0.0 Prediction for [1, 0, 1, 0, 0, 0, 0, 0, 1]: 0.0 Prediction for [1, 0, 1, 0, 0, 0, 0, 1, 0]: 0.0 Prediction for [1, 0, 1, 0, 0, 0, 0, 1, 1]: 0.0 Prediction for [1, 0, 1, 0, 0, 0, 1, 0, 0]: 0.0 Prediction for [1, 0, 1, 0, 0, 0, 1, 0, 1]: 0.0 Prediction for [1, 0, 1, 0, 0, 0, 1, 1, 0]: 0.0 Prediction for [1, 0, 1, 0, 0, 0, 1, 1, 1]: 0.010484141864332663 Prediction for [1, 0, 1, 0, 0, 1, 0, 0, 0]: 0.0 Prediction for [1, 0, 1, 0, 0, 1, 0, 0, 1]: 0.0 Prediction for [1, 0, 1, 0, 0, 1, 0, 1, 0]: 0.0 Prediction for [1, 0, 1, 0, 0, 1, 0, 1, 1]: 0.9999368432780287 Prediction for [1, 0, 1, 0, 0, 1, 1, 0, 0]: 0.0 Prediction for [1, 0, 1, 0, 0, 1, 1, 0, 1]: 0.0 Prediction for [1, 0, 1, 0, 0, 1, 1, 1, 0]: 0.0 Prediction for [1, 0, 1, 0, 0, 1, 1, 1, 1]: 0.00894501653227886 Prediction for [1, 0, 1, 0, 1, 0, 0, 0, 0]: 6.325675827958399E-4 Prediction for [1, 0, 1, 0, 1, 0, 0, 0, 1]: 0.9926826333628851 Prediction for [1, 0, 1, 0, 1, 0, 0, 1, 0]: 0.0 Prediction for [1, 0, 1, 0, 1, 0, 0, 1, 1]: 0.0 Prediction for [1, 0, 1, 0, 1, 0, 1, 0, 0]: 0.0 Prediction for [1, 0, 1, 0, 1, 0, 1, 0, 1]: 0.0011776294270866572 Prediction for [1, 0, 1, 0, 1, 0, 1, 1, 0]: 0.0 Prediction for [1, 0, 1, 0, 1, 0, 1, 1, 1]: 0.0 Prediction for [1, 0, 1, 0, 1, 1, 0, 0, 0]: 0.0 Prediction for [1, 0, 1, 0, 1, 1, 0, 0, 1]: 0.0 Prediction for [1, 0, 1, 0, 1, 1, 0, 1, 0]: 0.0 Prediction for [1, 0, 1, 0, 1, 1, 0, 1, 1]: 1.0025469896244266 Prediction for [1, 0, 1, 0, 1, 1, 1, 0, 0]: 0.0 Prediction for [1, 0, 1, 0, 1, 1, 1, 0, 1]: 1.0009280034665604 Prediction for [1, 0, 1, 0, 1, 1, 1, 1, 0]: 0.0 Prediction for [1, 0, 1, 0, 1, 1, 1, 1, 1]: 0.0 Prediction for [1, 0, 1, 1, 0, 0, 0, 0, 0]: 0.0 Prediction for [1, 0, 1, 1, 0, 0, 0, 0, 1]: 0.9815680022422706 Prediction for [1, 0, 1, 1, 0, 0, 0, 1, 0]: 0.0 Prediction for [1, 0, 1, 1, 0, 0, 0, 1, 1]: 0.0 Prediction for [1, 0, 1, 1, 0, 0, 1, 0, 0]: 0.0 Prediction for [1, 0, 1, 1, 0, 0, 1, 0, 1]: 0.0 Prediction for [1, 0, 1, 1, 0, 0, 1, 1, 0]: 0.0 Prediction for [1, 0, 1, 1, 0, 0, 1, 1, 1]: 0.9921492505637959 Prediction for [1, 0, 1, 1, 0, 1, 0, 0, 0]: 0.0 Prediction for [1, 0, 1, 1, 0, 1, 0, 0, 1]: 0.0 Prediction for [1, 0, 1, 1, 0, 1, 0, 1, 0]: 0.0 Prediction for [1, 0, 1, 1, 0, 1, 0, 1, 1]: 0.0 Prediction for [1, 0, 1, 1, 0, 1, 1, 0, 0]: 0.0 Prediction for [1, 0, 1, 1, 0, 1, 1, 0, 1]: 0.0 Prediction for [1, 0, 1, 1, 0, 1, 1, 1, 0]: 0.0 Prediction for [1, 0, 1, 1, 0, 1, 1, 1, 1]: 1.0058506535338259 Prediction for [1, 0, 1, 1, 1, 0, 0, 0, 0]: 0.0 Prediction for [1, 0, 1, 1, 1, 0, 0, 0, 1]: 0.0 Prediction for [1, 0, 1, 1, 1, 0, 0, 1, 0]: 0.0 Prediction for [1, 0, 1, 1, 1, 0, 0, 1, 1]: 0.0 Prediction for [1, 0, 1, 1, 1, 0, 1, 0, 0]: 0.0 Prediction for [1, 0, 1, 1, 1, 0, 1, 0, 1]: 0.9842785949786164 Prediction for [1, 0, 1, 1, 1, 0, 1, 1, 0]: 0.0 Prediction for [1, 0, 1, 1, 1, 0, 1, 1, 1]: 0.0 Prediction for [1, 0, 1, 1, 1, 1, 0, 0, 0]: 0.0 Prediction for [1, 0, 1, 1, 1, 1, 0, 0, 1]: 0.0 Prediction for [1, 0, 1, 1, 1, 1, 0, 1, 0]: 0.0 Prediction for [1, 0, 1, 1, 1, 1, 0, 1, 1]: 0.9860285790062422 Prediction for [1, 0, 1, 1, 1, 1, 1, 0, 0]: 0.0 Prediction for [1, 0, 1, 1, 1, 1, 1, 0, 1]: 0.0 Prediction for [1, 0, 1, 1, 1, 1, 1, 1, 0]: 0.0 Prediction for [1, 0, 1, 1, 1, 1, 1, 1, 1]: 1.0012687993220935 Prediction for [1, 1, 0, 0, 0, 0, 0, 0, 0]: 0.0 Prediction for [1, 1, 0, 0, 0, 0, 0, 0, 1]: 3.6797827335055544E-4 Prediction for [1, 1, 0, 0, 0, 0, 0, 1, 0]: 0.0 Prediction for [1, 1, 0, 0, 0, 0, 0, 1, 1]: 0.0 Prediction for [1, 1, 0, 0, 0, 0, 1, 0, 0]: 0.0 Prediction for [1, 1, 0, 0, 0, 0, 1, 0, 1]: 1.0067705093460706 Prediction for [1, 1, 0, 0, 0, 0, 1, 1, 0]: 0.0 Prediction for [1, 1, 0, 0, 0, 0, 1, 1, 1]: 0.0 Prediction for [1, 1, 0, 0, 0, 1, 0, 0, 0]: 0.0 Prediction for [1, 1, 0, 0, 0, 1, 0, 0, 1]: 0.0 Prediction for [1, 1, 0, 0, 0, 1, 0, 1, 0]: 0.0 Prediction for [1, 1, 0, 0, 0, 1, 0, 1, 1]: 0.0 Prediction for [1, 1, 0, 0, 0, 1, 1, 0, 0]: 0.0 Prediction for [1, 1, 0, 0, 0, 1, 1, 0, 1]: 1.0074994256525693 Prediction for [1, 1, 0, 0, 0, 1, 1, 1, 0]: 0.0 Prediction for [1, 1, 0, 0, 0, 1, 1, 1, 1]: 0.0 Prediction for [1, 1, 0, 0, 1, 0, 0, 0, 0]: 0.0 Prediction for [1, 1, 0, 0, 1, 0, 0, 0, 1]: 0.9792758396862498 Prediction for [1, 1, 0, 0, 1, 0, 0, 1, 0]: 0.0 Prediction for [1, 1, 0, 0, 1, 0, 0, 1, 1]: 0.027108220939364713 Prediction for [1, 1, 0, 0, 1, 0, 1, 0, 0]: 0.0 Prediction for [1, 1, 0, 0, 1, 0, 1, 0, 1]: 0.01103436325550744 Prediction for [1, 1, 0, 0, 1, 0, 1, 1, 0]: 0.0 Prediction for [1, 1, 0, 0, 1, 0, 1, 1, 1]: 0.0 Prediction for [1, 1, 0, 0, 1, 1, 0, 0, 0]: 0.0 Prediction for [1, 1, 0, 0, 1, 1, 0, 0, 1]: 0.9900451173410119 Prediction for [1, 1, 0, 0, 1, 1, 0, 1, 0]: 0.0 Prediction for [1, 1, 0, 0, 1, 1, 0, 1, 1]: 0.0 Prediction for [1, 1, 0, 0, 1, 1, 1, 0, 0]: 0.0 Prediction for [1, 1, 0, 0, 1, 1, 1, 0, 1]: 0.0 Prediction for [1, 1, 0, 0, 1, 1, 1, 1, 0]: 0.0 Prediction for [1, 1, 0, 0, 1, 1, 1, 1, 1]: 0.0 Prediction for [1, 1, 0, 1, 0, 0, 0, 0, 0]: 0.0 Prediction for [1, 1, 0, 1, 0, 0, 0, 0, 1]: 0.0 Prediction for [1, 1, 0, 1, 0, 0, 0, 1, 0]: 0.0 Prediction for [1, 1, 0, 1, 0, 0, 0, 1, 1]: 1.0025522830201572 Prediction for [1, 1, 0, 1, 0, 0, 1, 0, 0]: 0.0 Prediction for [1, 1, 0, 1, 0, 0, 1, 0, 1]: 0.9729903417171206 Prediction for [1, 1, 0, 1, 0, 0, 1, 1, 0]: 0.0 Prediction for [1, 1, 0, 1, 0, 0, 1, 1, 1]: 0.0 Prediction for [1, 1, 0, 1, 0, 1, 0, 0, 0]: 0.0 Prediction for [1, 1, 0, 1, 0, 1, 0, 0, 1]: 0.0 Prediction for [1, 1, 0, 1, 0, 1, 0, 1, 0]: 0.0 Prediction for [1, 1, 0, 1, 0, 1, 0, 1, 1]: 0.0 Prediction for [1, 1, 0, 1, 0, 1, 1, 0, 0]: 0.0 Prediction for [1, 1, 0, 1, 0, 1, 1, 0, 1]: 0.0 Prediction for [1, 1, 0, 1, 0, 1, 1, 1, 0]: 0.0 Prediction for [1, 1, 0, 1, 0, 1, 1, 1, 1]: 1.008686034895221 Prediction for [1, 1, 0, 1, 1, 0, 0, 0, 0]: 0.0 Prediction for [1, 1, 0, 1, 1, 0, 0, 0, 1]: 1.360766414161855 Prediction for [1, 1, 0, 1, 1, 0, 0, 1, 0]: 0.0 Prediction for [1, 1, 0, 1, 1, 0, 0, 1, 1]: 0.0 Prediction for [1, 1, 0, 1, 1, 0, 1, 0, 0]: 0.0 Prediction for [1, 1, 0, 1, 1, 0, 1, 0, 1]: 0.20498420737336076 Prediction for [1, 1, 0, 1, 1, 0, 1, 1, 0]: 0.0 Prediction for [1, 1, 0, 1, 1, 0, 1, 1, 1]: 0.8729569816038216 Prediction for [1, 1, 0, 1, 1, 1, 0, 0, 0]: 0.0 Prediction for [1, 1, 0, 1, 1, 1, 0, 0, 1]: 0.0 Prediction for [1, 1, 0, 1, 1, 1, 0, 1, 0]: 0.0 Prediction for [1, 1, 0, 1, 1, 1, 0, 1, 1]: 0.9954470605798269 Prediction for [1, 1, 0, 1, 1, 1, 1, 0, 0]: 0.0 Prediction for [1, 1, 0, 1, 1, 1, 1, 0, 1]: 8.63413805419988E-4 Prediction for [1, 1, 0, 1, 1, 1, 1, 1, 0]: 0.0 Prediction for [1, 1, 0, 1, 1, 1, 1, 1, 1]: 0.0 Prediction for [1, 1, 1, 0, 0, 0, 0, 0, 0]: 0.0 Prediction for [1, 1, 1, 0, 0, 0, 0, 0, 1]: 0.9951285994093197 Prediction for [1, 1, 1, 0, 0, 0, 0, 1, 0]: 0.0 Prediction for [1, 1, 1, 0, 0, 0, 0, 1, 1]: 0.0 Prediction for [1, 1, 1, 0, 0, 0, 1, 0, 0]: 0.0 Prediction for [1, 1, 1, 0, 0, 0, 1, 0, 1]: 0.008758316115685894 Prediction for [1, 1, 1, 0, 0, 0, 1, 1, 0]: 0.0 Prediction for [1, 1, 1, 0, 0, 0, 1, 1, 1]: 0.012906319551016399 Prediction for [1, 1, 1, 0, 0, 1, 0, 0, 0]: 0.0 Prediction for [1, 1, 1, 0, 0, 1, 0, 0, 1]: 0.9958829827559148 Prediction for [1, 1, 1, 0, 0, 1, 0, 1, 0]: 0.0 Prediction for [1, 1, 1, 0, 0, 1, 0, 1, 1]: 0.0 Prediction for [1, 1, 1, 0, 0, 1, 1, 0, 0]: 0.0 Prediction for [1, 1, 1, 0, 0, 1, 1, 0, 1]: 1.0013555786723716 Prediction for [1, 1, 1, 0, 0, 1, 1, 1, 0]: 0.0 Prediction for [1, 1, 1, 0, 0, 1, 1, 1, 1]: 0.9934860996879324 Prediction for [1, 1, 1, 0, 1, 0, 0, 0, 0]: 0.0 Prediction for [1, 1, 1, 0, 1, 0, 0, 0, 1]: 0.002462085708445194 Prediction for [1, 1, 1, 0, 1, 0, 0, 1, 0]: 0.0 Prediction for [1, 1, 1, 0, 1, 0, 0, 1, 1]: 1.0125432454301517 Prediction for [1, 1, 1, 0, 1, 0, 1, 0, 0]: 0.0 Prediction for [1, 1, 1, 0, 1, 0, 1, 0, 1]: 0.0 Prediction for [1, 1, 1, 0, 1, 0, 1, 1, 0]: 0.0 Prediction for [1, 1, 1, 0, 1, 0, 1, 1, 1]: 0.0 Prediction for [1, 1, 1, 0, 1, 1, 0, 0, 0]: 0.0 Prediction for [1, 1, 1, 0, 1, 1, 0, 0, 1]: 0.0 Prediction for [1, 1, 1, 0, 1, 1, 0, 1, 0]: 0.0 Prediction for [1, 1, 1, 0, 1, 1, 0, 1, 1]: 0.008469765837671783 Prediction for [1, 1, 1, 0, 1, 1, 1, 0, 0]: 0.0 Prediction for [1, 1, 1, 0, 1, 1, 1, 0, 1]: 0.0 Prediction for [1, 1, 1, 0, 1, 1, 1, 1, 0]: 0.0 Prediction for [1, 1, 1, 0, 1, 1, 1, 1, 1]: 1.0039194342673046 Prediction for [1, 1, 1, 1, 0, 0, 0, 0, 0]: 0.0 Prediction for [1, 1, 1, 1, 0, 0, 0, 0, 1]: 0.0 Prediction for [1, 1, 1, 1, 0, 0, 0, 1, 0]: 0.0 Prediction for [1, 1, 1, 1, 0, 0, 0, 1, 1]: 0.0 Prediction for [1, 1, 1, 1, 0, 0, 1, 0, 0]: 0.0 Prediction for [1, 1, 1, 1, 0, 0, 1, 0, 1]: 0.0 Prediction for [1, 1, 1, 1, 0, 0, 1, 1, 0]: 0.0 Prediction for [1, 1, 1, 1, 0, 0, 1, 1, 1]: 1.007929690559581 Prediction for [1, 1, 1, 1, 0, 1, 0, 0, 0]: 0.0 Prediction for [1, 1, 1, 1, 0, 1, 0, 0, 1]: 0.0 Prediction for [1, 1, 1, 1, 0, 1, 0, 1, 0]: 0.0 Prediction for [1, 1, 1, 1, 0, 1, 0, 1, 1]: 1.003705966757133 Prediction for [1, 1, 1, 1, 0, 1, 1, 0, 0]: 0.0 Prediction for [1, 1, 1, 1, 0, 1, 1, 0, 1]: 0.0070895358138693965 Prediction for [1, 1, 1, 1, 0, 1, 1, 1, 0]: 0.0 Prediction for [1, 1, 1, 1, 0, 1, 1, 1, 1]: 0.0 Prediction for [1, 1, 1, 1, 1, 0, 0, 0, 0]: 0.0 Prediction for [1, 1, 1, 1, 1, 0, 0, 0, 1]: 0.0 Prediction for [1, 1, 1, 1, 1, 0, 0, 1, 0]: 0.0 Prediction for [1, 1, 1, 1, 1, 0, 0, 1, 1]: 1.0103758625102754 Prediction for [1, 1, 1, 1, 1, 0, 1, 0, 0]: 0.0 Prediction for [1, 1, 1, 1, 1, 0, 1, 0, 1]: 0.0 Prediction for [1, 1, 1, 1, 1, 0, 1, 1, 0]: 0.0 Prediction for [1, 1, 1, 1, 1, 0, 1, 1, 1]: 0.995827451133688 Prediction for [1, 1, 1, 1, 1, 1, 0, 0, 0]: 0.0 Prediction for [1, 1, 1, 1, 1, 1, 0, 0, 1]: 0.0 Prediction for [1, 1, 1, 1, 1, 1, 0, 1, 0]: 0.0 Prediction for [1, 1, 1, 1, 1, 1, 0, 1, 1]: 0.0 Prediction for [1, 1, 1, 1, 1, 1, 1, 0, 0]: 0.0 Prediction for [1, 1, 1, 1, 1, 1, 1, 0, 1]: 0.7202539629771696 Prediction for [1, 1, 1, 1, 1, 1, 1, 1, 0]: 0.0 Prediction for [1, 1, 1, 1, 1, 1, 1, 1, 1]: 0.0 BUILD SUCCESSFUL (total time: 1 minute 19 seconds)

@Mark-XP No, I make a mistake in the listing, I just correct. And you have to choose at least 5 runs Dietmar

Spotify works (You need use --no-sandbox)

That's terrible news ! You both stay strong ! Try not to breathe the same air. Very important to not touch your face with your hands, wash them often. I hope she'll get better ! How do they know she has covidium ? Was it official ? Did she see a doctor ?

I currently have a girlfriend (born in 1996), met her in 2014, she came to my luxury city 'cause she wanted to be a model and she really did get quite some modelling with several famous French brands, also she was able to get a proper education in that area. Her father is absent (not sure what happened, I always forget, was he hit by a train or simply left?) . Now with the help of simple arithmetics, she is 27. Kinda old, so I'm keeping my options open since approx. 2018. Anyways ! Thanks for your concern !

Well, your girlfriend must be so cool, I only got a postcard and chocolate from my GF, while you got the whole PC on valentine's day !

Good morning to you too, jaclaz, always a pleasure to hear from you ! Sorry for the huge delay, I don't visit this topic often.

Hi, I test some programs for to convert an Java file *.jar to *.exe for school. This Java file Prim.jar is build with Netbeans 16 Ant under XP SP3 and works nice in this Netbeans 16 IDE under XP via Java 1.8.0_151 version. This new converted prim.exe program should run under XP SP3, Vista, win7, win8.1, win10, win11. Most convert programs do not work under XP SP3. When you run it as a Console Application for example this program prim.exe, which generates Prim Numbers, after finishing always closed the console at once, brrr.. Dietmar EDIT: Is there any possibility, to make an prim.exe , that runs without any Java Environment? For me it is strange as much as possible. When you build an prim.exe via C language, all those problems never happen. Here is my file Prim.jar https://ufile.io/l9xn8794 package prim; import java.util.Scanner; public class Prim { public static void main(String[] args) { Scanner scanner = new Scanner(System.in); System.out.print("Bis zu welcher Zahl möchten Sie die Primzahlen berechnen? : "); int n = scanner.nextInt(); System.out.println("Die Primzahlen bis " + n + " sind:"); for (int i = 2; i <= n; i++) { if (isPrimeNumber(i)) { System.out.print(i + " "); } } } public static boolean isPrimeNumber(int number) { if (number < 2) { return false; } for (int i = 2; i <= Math.sqrt(number); i++) { if (number % i == 0) { return false; } } return true; } }

Ohh.. soso much fun. Here is version of my Moorhuhn from 1998 with sound, not all ready but it can be done with a lot of work. You have to copy the file sound.wav in the same folder as moorhuhnSound.exe Dietmar https://ufile.io/a0toemvw import java.io.File; import javax.sound.sampled.AudioSystem; import javax.sound.sampled.Clip; import java.awt.Graphics; import java.awt.Image; import java.awt.event.MouseEvent; import java.awt.event.MouseListener; import java.util.ArrayList; import java.util.Random; import javax.swing.ImageIcon; import javax.swing.JFrame; import javax.swing.JPanel; public class Moorhuhn extends JPanel implements MouseListener { private ArrayList<Target> targets = new ArrayList<>(); private int score = 0; private Image background; private Clip clip; public Moorhuhn() { background = new ImageIcon("background.png").getImage(); addMouseListener(this); try { clip = AudioSystem.getClip(); clip.open(AudioSystem.getAudioInputStream(new File("sound.wav"))); clip.loop(Clip.LOOP_CONTINUOUSLY); } catch (Exception e) { System.err.println(e.getMessage()); } createTargets(); } private void createTargets() { Random r = new Random(); for (int i = 0; i < 10; i++) { int x = r.nextInt(400); int y = r.nextInt(400); targets.add(new Target(x, y)); } } @Override public void paint(Graphics g) { g.drawImage(background, 0, 0, null); for (Target t : targets) { t.draw(g); } } @Override public void mouseClicked(MouseEvent e) { for (Target t : targets) { if (t.contains(e.getX(), e.getY())) { score++; t.setVisible(false); repaint(); break; } } } @Override public void mousePressed(MouseEvent e) {} @Override public void mouseReleased(MouseEvent e) {} @Override public void mouseEntered(MouseEvent e) {} @Override public void mouseExited(MouseEvent e) {} } class Target { private int x, y; private Image image; private boolean visible; public Target(int x, int y) { this.x = x; this.y = y; image = new ImageIcon("target.png").getImage(); visible = true; } public void draw(Graphics g) { if (visible) { g.drawImage(image, x, y, null); } } public boolean contains(int x, int y) { int width = image.getWidth(null); int height = image.getHeight(null); return (x > this.x && x < this.x + width && y > this.y && y < this.y + height); } public void setVisible(boolean visible) { this.visible = visible; } } class Main { public static void main(String[] args) { JFrame frame = new JFrame("Moorhuhn"); frame.setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE); frame.setSize(400, 400); frame.add(new Moorhuhn()); frame.setVisible(true); } }

Hi, here is a very very first running famous game Moorhuhn from 1999, build with Java Netbeans 16, Ant all by myself and check with chatGPT Dietmar PS: The game runs, klick on the "Moorhuhn" and they disappear^^. You only need to have Java 1.4.0 installed, so may be it runs also under Win95 https://ufile.io/qr48x85w import java.awt.Graphics; import java.awt.Image; import java.awt.event.MouseEvent; import java.awt.event.MouseListener; import java.util.ArrayList; import java.util.Random; import javax.swing.ImageIcon; import javax.swing.JFrame; import javax.swing.JPanel; public class Moorhuhn extends JPanel implements MouseListener { private ArrayList<Target> targets = new ArrayList<>(); private int score = 0; private Image background; public Moorhuhn() { background = new ImageIcon("background.png").getImage(); addMouseListener(this); createTargets(); } private void createTargets() { Random r = new Random(); for (int i = 0; i < 10; i++) { int x = r.nextInt(400); int y = r.nextInt(400); targets.add(new Target(x, y)); } } @Override public void paint(Graphics g) { g.drawImage(background, 0, 0, null); for (Target t : targets) { t.draw(g); } } @Override public void mouseClicked(MouseEvent e) { for (Target t : targets) { if (t.contains(e.getX(), e.getY())) { score++; t.setVisible(false); repaint(); break; } } } @Override public void mousePressed(MouseEvent e) {} @Override public void mouseReleased(MouseEvent e) {} @Override public void mouseEntered(MouseEvent e) {} @Override public void mouseExited(MouseEvent e) {} } public class Main { public static void main(String[] args) { JFrame frame = new JFrame("Moorhuhn"); frame.setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE); frame.setSize(400, 400); frame.add(new Moorhuhn()); frame.setVisible(true); } } class Target { private int x, y; private Image image; private boolean visible; public Target(int x, int y) { this.x = x; this.y = y; image = new ImageIcon("target.png").getImage(); visible = true; } public void draw(Graphics g) { if (visible) { g.drawImage(image, x, y, null); } } public boolean contains(int x, int y) { int width = image.getWidth(null); int height = image.getHeight(null); return (x > this.x && x < this.x + width && y > this.y && y < this.y + height); } public void setVisible(boolean visible) { this.visible = visible; } }

Hi, just now I make small fun with game breakout. I make this complete by my own and check with chatGPT under Java Netbeans 16, Ant Dietmar PS: Here is the breakout.exe file. It runs under XP SP3. For this, you need to have at least Java 1.8.0 installed. https://ufile.io/ae3ygl6b package breakout; import java.awt.Color; import java.awt.Graphics; import java.awt.event.KeyEvent; import java.awt.event.KeyListener; import javax.swing.JFrame; public class Breakout extends JFrame implements KeyListener { int ballSize = 20; int x = 150; int y = 300; int xa = 1; int ya = -1; int paddleX = 120; boolean left = false; boolean right = false; int[][] bricks = new int[5][7]; int speed = 3; public Breakout() { setSize(300, 400); setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE); setVisible(true); setTitle("Breakout"); setResizable(false); addKeyListener(this); for (int i = 0; i < 5; i++) { for (int j = 0; j < 7; j++) { bricks[i][j] = 1; } } new Thread(() -> { while (true) { repaint(); try { Thread.sleep(10); } catch (InterruptedException ex) { ex.printStackTrace(); } } }).start(); } public void paint(Graphics g) { super.paint(g); // rufe die überschriebene paint-Methode der JFrame-Klasse auf g.setColor(Color.RED); g.fillOval(x, y, ballSize, ballSize); g.setColor(Color.BLUE); g.fillRect(paddleX, 380, 60, 10); for (int i = 0; i < 5; i++) { for (int j = 0; j < 7; j++) { if (bricks[i][j] == 1) { g.setColor(Color.YELLOW); g.fillRect(j * 40, i * 20, 40, 20); } } } if (left) { paddleX = paddleX - 10; } if (right) { paddleX = paddleX + 10; } if (paddleX < 0) { paddleX = 0; } if (paddleX > 300 - 60) { paddleX = 300 - 60; } x = x + xa; y = y + ya; if (x + ballSize > 300 || x < 0) { xa = -xa; } if (y + ballSize > 400 || y < 0) { if (x > paddleX && x < paddleX + 60 && y + ballSize > 380) { double relativeIntersectY = (paddleX + 30) - x; double normalizedRelativeIntersectionY = relativeIntersectY / (30); double bounceAngle = normalizedRelativeIntersectionY * 5 * Math.PI / 12; xa = (int) (speed * Math.sin(bounceAngle)); ya = -(int) (speed * Math.cos(bounceAngle)); y = 380 - ballSize; } else { System.exit(0); } } for (int i = 0; i < 5; i++) { for (int j = 0; j < 7; j++) { if (bricks[i][j] == 1 && x > j * 40 && x < j * 40 + 40 && y > i * 20 && y < i * 20 + 20) { bricks[i][j] = 0; ya = -ya; } } } } @Override public void keyTyped(KeyEvent e) { } @Override public void keyPressed(KeyEvent e) { if (e.getKeyCode() == KeyEvent.VK_LEFT) { left = true; } if (e.getKeyCode() == KeyEvent.VK_RIGHT) { right = true; } } @Override public void keyReleased(KeyEvent e) { if (e.getKeyCode() == KeyEvent.VK_LEFT) { left = false; } if (e.getKeyCode() == KeyEvent.VK_RIGHT) { right = false; } } public static void main(String[] args) { new Breakout(); } }

I make some more tests: With this Java Program, build just now with Netbeans 16 and JRE 1.8.0_151 also the via www.jar2exe.com build pong.exe runs only in an Java Environment. So, Launch4j-3.8-win32.exe is the better choice, because it is free. I do not succeed to make a pong.exe Program without any Java Environment but under Java 1.8.0 Environment it works Dietmar Here is all: Source, pong.jar, pong.exe https://ufile.io/os4ynlxq package pong; import java.awt.Color; import java.awt.Graphics; import javax.swing.JFrame; import javax.swing.JPanel; public class Pong extends JPanel { int x = 0, y = 0, xa = 1, ya = 1; private void moveBall() { x = x + xa; y = y + ya; if (x + xa > getWidth() - 30 || x + xa < 0) xa = -xa; if (y + ya > getHeight() - 30 || y + ya < 0) ya = -ya; } @Override public void paint(Graphics g) { super.paint(g); g.setColor(Color.RED); g.fillOval(x, y, 30, 30); } public static void main(String[] args) throws InterruptedException { JFrame frame = new JFrame("Pong"); Pong game = new Pong(); frame.add(game); frame.setSize(300, 400); frame.setVisible(true); frame.setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE); while (true) { game.moveBall(); game.repaint(); Thread.sleep(10); } } }

@D.Draker I tried a lot. A lot of prim.exe where build. No one works Dietmar PS: May be, here in the forum is somebody, who can make an prim.exe from my Prim.jar file, build with Netbeans 16 Ant under XP SP3 Dietmar Here is my Prim.jar file https://ufile.io/l9xn8794

@loblolly986 I tried JSmooth. Dont know, how to use it. I get message "Error, compiler couldn't be created. Error description should follow: - Selected skeleton is unknown." Dietmar

yes, hffps://board. DON'T.visit.it / is what I meant , you're right. A very weird website, right again. EDIT: And you have another opinion ?

I successfully ported newly released Opera Version: 96.0.4674.0 System:Windows Vista 64-bit Chromium version:110.0.5481.30

Yes, you're right, speaking of weird websites. Don't download anything from that weird eclipse.cx.