Leaderboard

This line alone makes me want to NOT do the like! Why are so many MSFN Members so glued to that d@mn "like"? This is not a social media web site. Or did I just fall prey to the oldest trick in the book - "reverse psychology"?

WU v4 now restored and working! (Only on Windows XP and Windows 2000) Here download it and try https://cdn.discordapp.com/attachments/1035182715537985577/1096868908000104568/v4final.7z

2040??? LTSC 2019 & Server 2019 support ends on the same date ( Jan 9, 2029 )

So, what made you think it could take decades for VxKex's developer to support Chromium 110+? This is a bit overexaggerated, don't you think? Maybe years, ok, but decades sounds like an overexaggeration to me.

I do not know what to say. Big thanks to @WinFX for the excellent work to get WUv4 working again. Honestly, I would never have believed that WUv4 would ever work again. A dream come true!

With limited testing on v112.3.4.3, the only time I witness any odd connections is when "secure DNS" is enabled - making me NOT TRUST this so-called "secure" DNS. It is better to set up your Operating System to use "secure DNS" than it is to rely on any web browser to perform that task for you, once that is "embedded" into the web browser, it can make ANY connection it wants to! There are some embedded "always accept cookies" web sites but I've not seen them create cookies so long as you do not visit those web sites. The embedded list is easily removable in chrome.dll - but I'm left with an "empty" web site instead of a none-added note, so still investigating.

StartAllBack 3.6.4

New build of Serpent/UXP for XP! Test binary: Win32 https://o.rthost.win/basilisk/basilisk52-g4.8.win32-git-20230415-3219d2d-uxp-75bef7b73-xpmod.7z Win64 https://o.rthost.win/basilisk/basilisk52-g4.8.win64-git-20230415-3219d2d-uxp-75bef7b73-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-20230415-3219d2d-uxp-75bef7b73-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-28.10.6a1.win32-git-20230415-d849524bd-uxp-75bef7b73-xpmod.7z Win32 IA32 https://o.rthost.win/palemoon/palemoon-28.10.6a1.win32-git-20230415-d849524bd-uxp-75bef7b73-xpmod-ia32.7z Win32 SSE https://o.rthost.win/palemoon/palemoon-28.10.6a1.win32-git-20230415-d849524bd-uxp-75bef7b73-xpmod-sse.7z Win64 https://o.rthost.win/palemoon/palemoon-28.10.6a1.win64-git-20230415-d849524bd-uxp-75bef7b73-xpmod.7z Official UXP changes picked since my last build: - Issue #1361 - Follow-up: Merge dom.getRootNode.enabled pref into dom.webcomponents.enabled. (8182d08b1) - Issue #252 - Move getElementsByName from HTMLDocument to Document (b2d750411) - Issue #252 - Follow-up: Include a null check against mDocument (7c759b2c2) - Issue #2197 - Part 1a: postMessages should have transferable as [] by default (438cdbd91) - Issue #2197 - Part 1b: Transferables should be arrays of objects (47147d58b) - Issue #2197 - Part 2a: Implement StructuredSerializeOptions for MessagePort (fd982fd29) - Issue #2197 - Part 2b: Implement StructuredSerializeOptions for Worker (158784cbe) - Issue #2197 - Part 2c: Implement StructuredSerializeOptions for ServiceWorker (4d58139fe) - Issue #2197 - Part 2d: Implement PostMessageOptions for Window (4174037d8) - Issue #2197 - Part 3: Implement self.structuredClone() (ef6b8db1d) - Issue #2197 - Part 4: Expose structuredClone in Sandbox (bbcfb6275) - Issue #2197 - Follow-up: Remove GC debug assertion on sandbox (8e6d73046) - Issue #595 - Implement window.event (31283d993) - Issue #2053 - Part 1: Performance should be an EventTarget (995f3117b) - Issue #2053 - Part 2: Update PerformanceMeasure to User Timing L3 (23519e0c2) - Issue #2053 - Part 3: Update PerformanceMark to User Timing L3 (3b57ba141) - Issue #2053 - Part 4a: Align IsPerformanceTimingAttribute to user-timing spec (4fc9cde7c) - Issue #2053 - Part 4b: Fix measure name to timestamp conversion (a0d52c009) - Issue #2053 - Part 5: Throw a DOMException instead of a JS exception for some errors (ef8e3b541) - Issue #2053 - Follow-up: Make the default ResourceTimingBufferSize larger (7823439b1) - Issue #2053 - Follow-up: Re-enable navigation timing now it's to-spec. (e51a63852) - Use nsAnonymousTemporaryFile for clipboard cache (42723b163) - Increase size of data over which we write the data to disk rather than keep it around in memory (af613ef24) - [network] Improve checks while parsing MIME parameters. (c9d961633) - [devtools] Don't allow sourcemap URLs to redirect (47bcca168) No official Pale-Moon changes picked since my last build. No official Basilisk changes picked since my last build. My changes since my last build: - Issue UXP#2053: fix deprots (5a74c0114) - mailnews: follow-up rev c9d96163, fix build (6beccbf6c) - Bug 1159003 - setResourceTimingBufferSize shouldn't affect user timing, but we should clean user markers if we have memory pressure, r=bz (bc3eb89de) - Bug 1159003 - Remove Performance::GetAsISupports(), r=bz (16a1923c3) - Bug 1378537 - Store PerformanceEntry objects in AutoTArray; r=smaug (75bef7b73) 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.

Download links - https://www.dropbox.com/s/ddn966t73s5g22f/360ChromePortable_13.5.2036_r1_ungoogled.zip?dl=1 https://www.dropbox.com/s/5pnmj58ugy6bi9g/360ChromePortable_13.5.2036_r1_regular.zip?dl=1 Regular version maintains Chrome Web Store and embedded Google Translate. Ungoogled intentionally breaks Chrome Web Store and removed embedded Google Translate.

BEWARE of that dodgy browser ! Using it will make you 100% unique ! Why ? The sneaky china fella injected a unique identifier right into the browser code ! Go here and you will see : https://browserleaks.com/javascript catsxp [object Catsxp] Everyone will know you're using his browser ! This won't happen with a normal chrome, be it googled or ungoogled. Will you find what he did and where it's located ???? Guessing no likes for me for uncovering the plot of a "good" china fella, your "saviour" of Win7 userbase. D.Draker is all that "bad" , saying "nasty" things (the truth, actually) about "poor" and "honest" developers from Asia.

I do not use dark themes and can not entertain questions pertaining towards their use.

thanks again. ! see that the chrome.dll is rebased compared to 13.5.2022 , works fine. so does the win 10 skin that was posted earlier. my "white text to black mod" in the top blue bar also works.

Download links added to first post.

Links for the latest 13.5 build 2036 will be added to the new thread shortly. https://msfn.org/board/topic/184624-arcticfoxienotheretoplaygames-360chrome-v1352036-rebuild-1/

Introducing StartAllBack: an app to fix all Windows 11 UI issues! Restore taskbar functionality - Drag and drop, different icon sizes, different screen sides, widgets, new icons, old flyouts, oh my! Restore context menus - Win32 menus were never this sexy! Fix Windows Explorer - Ribbon UI and Command Bar made sexy and not slow; search box that works Top notch styling - Recolor everything: all UI elements in all apps don't have to be blue! - Fix broken Win32 styling in Win11 RTM version - Improved dark mode styling with Explorer And start menu: yes! - Windows 7 style all-signing, all-dancing yet again, refreshed with new look and functions It could be the last year you can enjoy Windows not crippled, so do it! https://www.startallback.com

Hello, I want to recreate the Microsoft Windows Update v3/v4/v5 sites in local with all the elements. I know the Wayback Machine Downloader to do this but I can't find any pages of this site on web.archive.org. So, can you help me doing that project? Note: this is a public project, anyone can participate, but pls, don't share other Windows Update sites than v3, v4, v5 or v6.

Only if you installed with the "defaults" and did not take the extra mouse click to go into install options.

@Dietmar as far as i can see no magic: you're not excluding anything here for (int i = 0; i < trainingInputs.length; i++) { if (trainingInputs[i][0] != 211 && trainingInputs[i][0] != 212 && ... since trainingInputs [j] [0] is allways 0 or 1 and hence the above condition doesn't catch. it would be indeed use- and helpful to add the decimal value of the number in the first element trainingInputs [j] [0]

Still hoping for working v4 Windows 98SE/ME but that's already good progress! It's been more than 11 years since it got shut down, time flies

My congratulations to you all, who devoted their time in this project to revive old Windows Update, especially @maile3241 @WinFX @ByQuadCore @WULover and @LonghornXP. I'm very glad to see old Windows Update working again!

I know

It all depends on the desire of VxKex's developer, honestly.

Great work @Tihiy I remember you from the Revolutions Pack days I've just tried StartAllBack after using ExplorerPatcher for a while (also good stuff) and immediately bought a license, it makes Windows 11 look like Windows 11 while actually being useful! Just one thing I've noticed: - Is there a way to change StartAllBack Settings' language? Couldn't find an option for it and it is forced with the currently set locale.

I can not replicate, everything working here. Please note that you can NOT upgrade from build 1030 and keep your 1030 profile because indexes are off by 1, 7, 10, or 12 depending on index. If you have the incorrect index, then three hundred and thirty out of three hundred and eighty seven text strings will not land where they are supposed to, the Task Manager being but only one of them. You CAN upgrade from build 2022 and keep your 2022 profile.

@roytam1At which page did that happen? Would be perhaps a good idea to open then a bug report on the UXP repo again.

Yeah, maybe they will receive some ESU till 2032 or so but 2040.. nah

@Mark-XP And this one is for the primes, waaaoooohhhh Dietmar package multiof3; import java.util.Arrays; import java.util.Random; public class Multiof3 { private final int numInputNodes = 8; private final int numHiddenNodes = 26; private final int numOutputNodes = 1; private final double learningRate = 0.03; private final int numEpochs = 200000; private final double errorThreshold = 0.00000000000000000000000000000001; private double[][] inputToHiddenWeights; private double[][] hiddenToOutputWeights; private double[] hiddenBiases; private double[] outputBiases; public Multiof3() { Random random = new Random(); inputToHiddenWeights = new double[numInputNodes][numHiddenNodes]; hiddenToOutputWeights = new double[numHiddenNodes][numOutputNodes]; hiddenBiases = new double[numHiddenNodes]; outputBiases = new double[numOutputNodes]; for (int i = 0; i < numInputNodes; i++) { for (int j = 0; j < numHiddenNodes; j++) { inputToHiddenWeights[i][j] = random.nextDouble() - 0.5; } } for (int i = 0; i < numHiddenNodes; i++) { for (int j = 0; j < numOutputNodes; j++) { hiddenToOutputWeights[i][j] = random.nextDouble() - 0.5; } hiddenBiases[i] = random.nextDouble() - 0.5; } for (int i = 0; i < numOutputNodes; i++) { outputBiases[i] = random.nextDouble() - 0.5; } } public double relu(double x) { return Math.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++) { double[] input = trainingInputs[i]; double target = trainingTargets[i]; // Forward propagation double[] hiddenOutputs = new double[numHiddenNodes]; for (int j = 0; j < numHiddenNodes; j++) { double weightedSum = 0.0; for (int k = 0; k < numInputNodes; k++) { weightedSum += inputToHiddenWeights[k][j] * input[k]; } hiddenOutputs[j] = relu(weightedSum + hiddenBiases[j]); } double output = 0.0; for (int j = 0; j < numOutputNodes; j++) { double weightedSum = 0.0; for (int k = 0; k < numHiddenNodes; k++) { weightedSum += hiddenToOutputWeights[k][j] * hiddenOutputs[k]; } output = relu(weightedSum + outputBiases[j]); } // Backward propagation double outputErrorGradient = (output - target) * reluDerivative(output); for (int j = 0; j < numHiddenNodes; j++) { double hiddenErrorGradient = outputErrorGradient * hiddenToOutputWeights[j][0] * reluDerivative(hiddenOutputs[j]); for (int k = 0; k < numInputNodes; k++) { inputToHiddenWeights[k][j] -= learningRate * input[k] * hiddenErrorGradient; } hiddenBiases[j] -= learningRate * hiddenErrorGradient; } hiddenToOutputWeights[0][0] -= learningRate * hiddenOutputs[0] * outputErrorGradient; outputBiases[0] -= learningRate * outputErrorGradient; // Update total error totalError += Math.pow(output - target, 2); } // Calculate mean error and check for convergence double meanError = totalError / trainingInputs.length; if (meanError < errorThreshold) { System.out.println("Training complete. Mean error: " + meanError); break; } else if (epoch % 10000 == 0) { System.out.println("Epoch " + epoch + ". Mean error: " + meanError); } } } public double predict(double[] input) { double[] hiddenOutputs = new double[numHiddenNodes]; for (int j = 0; j < numHiddenNodes; j++) { double weightedSum = 0.0; for (int k = 0; k < numInputNodes; k++) { weightedSum += inputToHiddenWeights[k][j] * input[k]; } hiddenOutputs[j] = relu(weightedSum + hiddenBiases[j]); } double output = 0.0; for (int j = 0; j < numOutputNodes; j++) { double weightedSum = 0.0; for (int k = 0; k < numHiddenNodes; k++) { weightedSum += hiddenToOutputWeights[k][j] * hiddenOutputs[k]; } output = relu(weightedSum + outputBiases[j]); } return output; } 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, 1}, {0, 0, 0, 0, 0, 0, 1, 0}, {0, 0, 0, 0, 0, 0, 1, 1}, {0, 0, 0, 0, 0, 1, 0, 0}, {0, 0, 0, 0, 0, 1, 0, 1}, {0, 0, 0, 0, 0, 1, 1, 0}, {0, 0, 0, 0, 0, 1, 1, 1}, {0, 0, 0, 0, 1, 0, 0, 0}, {0, 0, 0, 0, 1, 0, 0, 1}, {0, 0, 0, 0, 1, 0, 1, 0}, {0, 0, 0, 0, 1, 0, 1, 1}, {0, 0, 0, 0, 1, 1, 0, 0}, {0, 0, 0, 0, 1, 1, 0, 1}, {0, 0, 0, 0, 1, 1, 1, 0}, {0, 0, 0, 0, 1, 1, 1, 1}, {0, 0, 0, 1, 0, 0, 0, 0}, {0, 0, 0, 1, 0, 0, 0, 1}, {0, 0, 0, 1, 0, 0, 1, 0}, {0, 0, 0, 1, 0, 0, 1, 1}, {0, 0, 0, 1, 0, 1, 0, 0}, {0, 0, 0, 1, 0, 1, 0, 1}, {0, 0, 0, 1, 0, 1, 1, 0}, {0, 0, 0, 1, 0, 1, 1, 1}, {0, 0, 0, 1, 1, 0, 0, 0}, {0, 0, 0, 1, 1, 0, 0, 1}, {0, 0, 0, 1, 1, 0, 1, 0}, {0, 0, 0, 1, 1, 0, 1, 1}, {0, 0, 0, 1, 1, 1, 0, 0}, {0, 0, 0, 1, 1, 1, 0, 1}, {0, 0, 0, 1, 1, 1, 1, 0}, {0, 0, 0, 1, 1, 1, 1, 1}, {0, 0, 1, 0, 0, 0, 0, 0}, {0, 0, 1, 0, 0, 0, 0, 1}, {0, 0, 1, 0, 0, 0, 1, 0}, {0, 0, 1, 0, 0, 0, 1, 1}, {0, 0, 1, 0, 0, 1, 0, 0}, {0, 0, 1, 0, 0, 1, 0, 1}, {0, 0, 1, 0, 0, 1, 1, 0}, {0, 0, 1, 0, 0, 1, 1, 1}, {0, 0, 1, 0, 1, 0, 0, 0}, {0, 0, 1, 0, 1, 0, 0, 1}, {0, 0, 1, 0, 1, 0, 1, 0}, {0, 0, 1, 0, 1, 0, 1, 1}, {0, 0, 1, 0, 1, 1, 0, 0}, {0, 0, 1, 0, 1, 1, 0, 1}, {0, 0, 1, 0, 1, 1, 1, 0}, {0, 0, 1, 0, 1, 1, 1, 1}, {0, 0, 1, 1, 0, 0, 0, 0}, {0, 0, 1, 1, 0, 0, 0, 1}, {0, 0, 1, 1, 0, 0, 1, 0}, {0, 0, 1, 1, 0, 0, 1, 1}, {0, 0, 1, 1, 0, 1, 0, 0}, {0, 0, 1, 1, 0, 1, 0, 1}, {0, 0, 1, 1, 0, 1, 1, 0}, {0, 0, 1, 1, 0, 1, 1, 1}, {0, 0, 1, 1, 1, 0, 0, 0}, {0, 0, 1, 1, 1, 0, 0, 1}, {0, 0, 1, 1, 1, 0, 1, 0}, {0, 0, 1, 1, 1, 0, 1, 1}, {0, 0, 1, 1, 1, 1, 0, 0}, {0, 0, 1, 1, 1, 1, 0, 1}, {0, 0, 1, 1, 1, 1, 1, 0}, {0, 0, 1, 1, 1, 1, 1, 1}, {0, 1, 0, 0, 0, 0, 0, 0}, {0, 1, 0, 0, 0, 0, 0, 1}, {0, 1, 0, 0, 0, 0, 1, 0}, {0, 1, 0, 0, 0, 0, 1, 1}, {0, 1, 0, 0, 0, 1, 0, 0}, {0, 1, 0, 0, 0, 1, 0, 1}, {0, 1, 0, 0, 0, 1, 1, 0}, {0, 1, 0, 0, 0, 1, 1, 1}, {0, 1, 0, 0, 1, 0, 0, 0}, {0, 1, 0, 0, 1, 0, 0, 1}, {0, 1, 0, 0, 1, 0, 1, 0}, {0, 1, 0, 0, 1, 0, 1, 1}, {0, 1, 0, 0, 1, 1, 0, 0}, {0, 1, 0, 0, 1, 1, 0, 1}, {0, 1, 0, 0, 1, 1, 1, 0}, {0, 1, 0, 0, 1, 1, 1, 1}, {0, 1, 0, 1, 0, 0, 0, 0}, {0, 1, 0, 1, 0, 0, 0, 1}, {0, 1, 0, 1, 0, 0, 1, 0}, {0, 1, 0, 1, 0, 0, 1, 1}, {0, 1, 0, 1, 0, 1, 0, 0}, {0, 1, 0, 1, 0, 1, 0, 1}, {0, 1, 0, 1, 0, 1, 1, 0}, {0, 1, 0, 1, 0, 1, 1, 1}, {0, 1, 0, 1, 1, 0, 0, 0}, {0, 1, 0, 1, 1, 0, 0, 1}, {0, 1, 0, 1, 1, 0, 1, 0}, {0, 1, 0, 1, 1, 0, 1, 1}, {0, 1, 0, 1, 1, 1, 0, 0}, {0, 1, 0, 1, 1, 1, 0, 1}, {0, 1, 0, 1, 1, 1, 1, 0}, {0, 1, 0, 1, 1, 1, 1, 1}, {0, 1, 1, 0, 0, 0, 0, 0}, {0, 1, 1, 0, 0, 0, 0, 1}, {0, 1, 1, 0, 0, 0, 1, 0}, {0, 1, 1, 0, 0, 0, 1, 1}, {0, 1, 1, 0, 0, 1, 0, 0}, {0, 1, 1, 0, 0, 1, 0, 1}, {0, 1, 1, 0, 0, 1, 1, 0}, {0, 1, 1, 0, 0, 1, 1, 1}, {0, 1, 1, 0, 1, 0, 0, 0}, {0, 1, 1, 0, 1, 0, 0, 1}, {0, 1, 1, 0, 1, 0, 1, 0}, {0, 1, 1, 0, 1, 0, 1, 1}, {0, 1, 1, 0, 1, 1, 0, 0}, {0, 1, 1, 0, 1, 1, 0, 1}, {0, 1, 1, 0, 1, 1, 1, 0}, {0, 1, 1, 0, 1, 1, 1, 1}, {0, 1, 1, 1, 0, 0, 0, 0}, {0, 1, 1, 1, 0, 0, 0, 1}, {0, 1, 1, 1, 0, 0, 1, 0}, {0, 1, 1, 1, 0, 0, 1, 1}, {0, 1, 1, 1, 0, 1, 0, 0}, {0, 1, 1, 1, 0, 1, 0, 1}, {0, 1, 1, 1, 0, 1, 1, 0}, {0, 1, 1, 1, 0, 1, 1, 1}, {0, 1, 1, 1, 1, 0, 0, 0}, {0, 1, 1, 1, 1, 0, 0, 1}, {0, 1, 1, 1, 1, 0, 1, 0}, {0, 1, 1, 1, 1, 0, 1, 1}, {0, 1, 1, 1, 1, 1, 0, 0}, {0, 1, 1, 1, 1, 1, 0, 1}, {0, 1, 1, 1, 1, 1, 1, 0}, {0, 1, 1, 1, 1, 1, 1, 1}, {1, 0, 0, 0, 0, 0, 0, 0}, {1, 0, 0, 0, 0, 0, 0, 1}, {1, 0, 0, 0, 0, 0, 1, 0}, {1, 0, 0, 0, 0, 0, 1, 1}, {1, 0, 0, 0, 0, 1, 0, 0}, {1, 0, 0, 0, 0, 1, 0, 1}, {1, 0, 0, 0, 0, 1, 1, 0}, {1, 0, 0, 0, 0, 1, 1, 1}, {1, 0, 0, 0, 1, 0, 0, 0}, {1, 0, 0, 0, 1, 0, 0, 1}, {1, 0, 0, 0, 1, 0, 1, 0}, {1, 0, 0, 0, 1, 0, 1, 1}, {1, 0, 0, 0, 1, 1, 0, 0}, {1, 0, 0, 0, 1, 1, 0, 1}, {1, 0, 0, 0, 1, 1, 1, 0}, {1, 0, 0, 0, 1, 1, 1, 1}, {1, 0, 0, 1, 0, 0, 0, 0}, {1, 0, 0, 1, 0, 0, 0, 1}, {1, 0, 0, 1, 0, 0, 1, 0}, {1, 0, 0, 1, 0, 0, 1, 1}, {1, 0, 0, 1, 0, 1, 0, 0}, {1, 0, 0, 1, 0, 1, 0, 1}, {1, 0, 0, 1, 0, 1, 1, 0}, {1, 0, 0, 1, 0, 1, 1, 1}, {1, 0, 0, 1, 1, 0, 0, 0}, {1, 0, 0, 1, 1, 0, 0, 1}, {1, 0, 0, 1, 1, 0, 1, 0}, {1, 0, 0, 1, 1, 0, 1, 1}, {1, 0, 0, 1, 1, 1, 0, 0}, {1, 0, 0, 1, 1, 1, 0, 1}, {1, 0, 0, 1, 1, 1, 1, 0}, {1, 0, 0, 1, 1, 1, 1, 1}, {1, 0, 1, 0, 0, 0, 0, 0}, {1, 0, 1, 0, 0, 0, 0, 1}, {1, 0, 1, 0, 0, 0, 1, 0}, {1, 0, 1, 0, 0, 0, 1, 1}, {1, 0, 1, 0, 0, 1, 0, 0}, {1, 0, 1, 0, 0, 1, 0, 1}, {1, 0, 1, 0, 0, 1, 1, 0}, {1, 0, 1, 0, 0, 1, 1, 1}, {1, 0, 1, 0, 1, 0, 0, 0}, {1, 0, 1, 0, 1, 0, 0, 1}, {1, 0, 1, 0, 1, 0, 1, 0}, {1, 0, 1, 0, 1, 0, 1, 1}, {1, 0, 1, 0, 1, 1, 0, 0}, {1, 0, 1, 0, 1, 1, 0, 1}, {1, 0, 1, 0, 1, 1, 1, 0}, {1, 0, 1, 0, 1, 1, 1, 1}, {1, 0, 1, 1, 0, 0, 0, 0}, {1, 0, 1, 1, 0, 0, 0, 1}, {1, 0, 1, 1, 0, 0, 1, 0}, {1, 0, 1, 1, 0, 0, 1, 1}, {1, 0, 1, 1, 0, 1, 0, 0}, {1, 0, 1, 1, 0, 1, 0, 1}, {1, 0, 1, 1, 0, 1, 1, 0}, {1, 0, 1, 1, 0, 1, 1, 1}, {1, 0, 1, 1, 1, 0, 0, 0}, {1, 0, 1, 1, 1, 0, 0, 1}, {1, 0, 1, 1, 1, 0, 1, 0}, {1, 0, 1, 1, 1, 0, 1, 1}, {1, 0, 1, 1, 1, 1, 0, 0}, {1, 0, 1, 1, 1, 1, 0, 1}, {1, 0, 1, 1, 1, 1, 1, 0}, {1, 0, 1, 1, 1, 1, 1, 1}, {1, 1, 0, 0, 0, 0, 0, 0}, {1, 1, 0, 0, 0, 0, 0, 1}, {1, 1, 0, 0, 0, 0, 1, 0}, {1, 1, 0, 0, 0, 0, 1, 1}, {1, 1, 0, 0, 0, 1, 0, 0}, {1, 1, 0, 0, 0, 1, 0, 1}, {1, 1, 0, 0, 0, 1, 1, 0}, {1, 1, 0, 0, 0, 1, 1, 1}, {1, 1, 0, 0, 1, 0, 0, 0}, {1, 1, 0, 0, 1, 0, 0, 1}, {1, 1, 0, 0, 1, 0, 1, 0}, {1, 1, 0, 0, 1, 0, 1, 1}, {1, 1, 0, 0, 1, 1, 0, 0}, {1, 1, 0, 0, 1, 1, 0, 1}, {1, 1, 0, 0, 1, 1, 1, 0}, {1, 1, 0, 0, 1, 1, 1, 1}, {1, 1, 0, 1, 0, 0, 0, 0}, {1, 1, 0, 1, 0, 0, 0, 1}, {1, 1, 0, 1, 0, 0, 1, 0}, {1, 1, 0, 1, 0, 0, 1, 1}, {1, 1, 0, 1, 0, 1, 0, 0}, {1, 1, 0, 1, 0, 1, 0, 1}, {1, 1, 0, 1, 0, 1, 1, 0}, {1, 1, 0, 1, 0, 1, 1, 1}, {1, 1, 0, 1, 1, 0, 0, 0}, {1, 1, 0, 1, 1, 0, 0, 1}, {1, 1, 0, 1, 1, 0, 1, 0}, {1, 1, 0, 1, 1, 0, 1, 1}, {1, 1, 0, 1, 1, 1, 0, 0}, {1, 1, 0, 1, 1, 1, 0, 1}, {1, 1, 0, 1, 1, 1, 1, 0}, {1, 1, 0, 1, 1, 1, 1, 1}, {1, 1, 1, 0, 0, 0, 0, 0}, {1, 1, 1, 0, 0, 0, 0, 1}, {1, 1, 1, 0, 0, 0, 1, 0}, {1, 1, 1, 0, 0, 0, 1, 1}, {1, 1, 1, 0, 0, 1, 0, 0}, {1, 1, 1, 0, 0, 1, 0, 1}, {1, 1, 1, 0, 0, 1, 1, 0}, {1, 1, 1, 0, 0, 1, 1, 1}, {1, 1, 1, 0, 1, 0, 0, 0}, {1, 1, 1, 0, 1, 0, 0, 1}, {1, 1, 1, 0, 1, 0, 1, 0}, {1, 1, 1, 0, 1, 0, 1, 1}, {1, 1, 1, 0, 1, 1, 0, 0}, {1, 1, 1, 0, 1, 1, 0, 1}, {1, 1, 1, 0, 1, 1, 1, 0}, {1, 1, 1, 0, 1, 1, 1, 1}, {1, 1, 1, 1, 0, 0, 0, 0}, {1, 1, 1, 1, 0, 0, 0, 1}, {1, 1, 1, 1, 0, 0, 1, 0}, {1, 1, 1, 1, 0, 0, 1, 1}, {1, 1, 1, 1, 0, 1, 0, 0}, {1, 1, 1, 1, 0, 1, 0, 1}, {1, 1, 1, 1, 0, 1, 1, 0}, {1, 1, 1, 1, 0, 1, 1, 1}, {1, 1, 1, 1, 1, 0, 0, 0}, {1, 1, 1, 1, 1, 0, 0, 1}, {1, 1, 1, 1, 1, 0, 1, 0}, {1, 1, 1, 1, 1, 0, 1, 1}, {1, 1, 1, 1, 1, 1, 0, 0}, {1, 1, 1, 1, 1, 1, 0, 1}, {1, 1, 1, 1, 1, 1, 1, 0}, {1, 1, 1, 1, 1, 1, 1, 1}}; double[] trainingTargets = { 0, 1, 1, 1, 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 }; Multiof3 nn = new Multiof3(); nn.train(trainingInputs, trainingTargets); System.out.println("Prediction for [0, 0, 0, 0, 0, 0, 0, 0]: " + nn.predict(new double[]{0, 0, 0, 0, 0, 0, 0, 0})); System.out.println("Prediction for [0, 0, 0, 0, 0, 0, 0, 1]: " + nn.predict(new double[]{0, 0, 0, 0, 0, 0, 0, 1})); System.out.println("Prediction for [0, 0, 0, 0, 0, 0, 1, 0]: " + nn.predict(new double[]{0, 0, 0, 0, 0, 0, 1, 0})); System.out.println("Prediction for [0, 0, 0, 0, 0, 0, 1, 1]: " + nn.predict(new double[]{0, 0, 0, 0, 0, 0, 1, 1})); System.out.println("Prediction for [0, 0, 0, 0, 0, 1, 0, 0]: " + nn.predict(new double[]{0, 0, 0, 0, 0, 1, 0, 0})); System.out.println("Prediction for [0, 0, 0, 0, 0, 1, 0, 1]: " + nn.predict(new double[]{0, 0, 0, 0, 0, 1, 0, 1})); System.out.println("Prediction for [0, 0, 0, 0, 0, 1, 1, 0]: " + nn.predict(new double[]{0, 0, 0, 0, 0, 1, 1, 0})); System.out.println("Prediction for [0, 0, 0, 0, 0, 1, 1, 1]: " + nn.predict(new double[]{0, 0, 0, 0, 0, 1, 1, 1})); System.out.println("Prediction for [0, 0, 0, 0, 1, 0, 0, 0]: " + nn.predict(new double[]{0, 0, 0, 0, 1, 0, 0, 0})); System.out.println("Prediction for [0, 0, 0, 0, 1, 0, 0, 1]: " + nn.predict(new double[]{0, 0, 0, 0, 1, 0, 0, 1})); System.out.println("Prediction for [0, 0, 0, 0, 1, 0, 1, 0]: " + nn.predict(new double[]{0, 0, 0, 0, 1, 0, 1, 0})); System.out.println("Prediction for [0, 0, 0, 0, 1, 0, 1, 1]: " + nn.predict(new double[]{0, 0, 0, 0, 1, 0, 1, 1})); System.out.println("Prediction for [0, 0, 0, 0, 1, 1, 0, 0]: " + nn.predict(new double[]{0, 0, 0, 0, 1, 1, 0, 0})); System.out.println("Prediction for [0, 0, 0, 0, 1, 1, 0, 1]: " + nn.predict(new double[]{0, 0, 0, 0, 1, 1, 0, 1})); System.out.println("Prediction for [0, 0, 0, 0, 1, 1, 1, 0]: " + nn.predict(new double[]{0, 0, 0, 0, 1, 1, 1, 0})); System.out.println("Prediction for [0, 0, 0, 0, 1, 1, 1, 1]: " + nn.predict(new double[]{0, 0, 0, 0, 1, 1, 1, 1})); System.out.println("Prediction for [0, 0, 0, 1, 0, 0, 0, 0]: " + nn.predict(new double[]{0, 0, 0, 1, 0, 0, 0, 0})); System.out.println("Prediction for [0, 0, 0, 1, 0, 0, 0, 1]: " + nn.predict(new double[]{0, 0, 0, 1, 0, 0, 0, 1})); System.out.println("Prediction for [0, 0, 0, 1, 0, 0, 1, 0]: " + nn.predict(new double[]{0, 0, 0, 1, 0, 0, 1, 0})); System.out.println("Prediction for [0, 0, 0, 1, 0, 0, 1, 1]: " + nn.predict(new double[]{0, 0, 0, 1, 0, 0, 1, 1})); System.out.println("Prediction for [0, 0, 0, 1, 0, 1, 0, 0]: " + nn.predict(new double[]{0, 0, 0, 1, 0, 1, 0, 0})); System.out.println("Prediction for [0, 0, 0, 1, 0, 1, 0, 1]: " + nn.predict(new double[]{0, 0, 0, 1, 0, 1, 0, 1})); System.out.println("Prediction for [0, 0, 0, 1, 0, 1, 1, 0]: " + nn.predict(new double[]{0, 0, 0, 1, 0, 1, 1, 0})); System.out.println("Prediction for [0, 0, 0, 1, 0, 1, 1, 1]: " + nn.predict(new double[]{0, 0, 0, 1, 0, 1, 1, 1})); System.out.println("Prediction for [0, 0, 0, 1, 1, 0, 0, 0]: " + nn.predict(new double[]{0, 0, 0, 1, 1, 0, 0, 0})); System.out.println("Prediction for [0, 0, 0, 1, 1, 0, 0, 1]: " + nn.predict(new double[]{0, 0, 0, 1, 1, 0, 0, 1})); System.out.println("Prediction for [0, 0, 0, 1, 1, 0, 1, 0]: " + nn.predict(new double[]{0, 0, 0, 1, 1, 0, 1, 0})); System.out.println("Prediction for [0, 0, 0, 1, 1, 0, 1, 1]: " + nn.predict(new double[]{0, 0, 0, 1, 1, 0, 1, 1})); System.out.println("Prediction for [0, 0, 0, 1, 1, 1, 0, 0]: " + nn.predict(new double[]{0, 0, 0, 1, 1, 1, 0, 0})); System.out.println("Prediction for [0, 0, 0, 1, 1, 1, 0, 1]: " + nn.predict(new double[]{0, 0, 0, 1, 1, 1, 0, 1})); System.out.println("Prediction for [0, 0, 0, 1, 1, 1, 1, 0]: " + nn.predict(new double[]{0, 0, 0, 1, 1, 1, 1, 0})); System.out.println("Prediction for [0, 0, 0, 1, 1, 1, 1, 1]: " + nn.predict(new double[]{0, 0, 0, 1, 1, 1, 1, 1})); System.out.println("Prediction for [0, 0, 1, 0, 0, 0, 0, 0]: " + nn.predict(new double[]{0, 0, 1, 0, 0, 0, 0, 0})); System.out.println("Prediction for [0, 0, 1, 0, 0, 0, 0, 1]: " + nn.predict(new double[]{0, 0, 1, 0, 0, 0, 0, 1})); System.out.println("Prediction for [0, 0, 1, 0, 0, 0, 1, 0]: " + nn.predict(new double[]{0, 0, 1, 0, 0, 0, 1, 0})); System.out.println("Prediction for [0, 0, 1, 0, 0, 0, 1, 1]: " + nn.predict(new double[]{0, 0, 1, 0, 0, 0, 1, 1})); System.out.println("Prediction for [0, 0, 1, 0, 0, 1, 0, 0]: " + nn.predict(new double[]{0, 0, 1, 0, 0, 1, 0, 0})); System.out.println("Prediction for [0, 0, 1, 0, 0, 1, 0, 1]: " + nn.predict(new double[]{0, 0, 1, 0, 0, 1, 0, 1})); System.out.println("Prediction for [0, 0, 1, 0, 0, 1, 1, 0]: " + nn.predict(new double[]{0, 0, 1, 0, 0, 1, 1, 0})); System.out.println("Prediction for [0, 0, 1, 0, 0, 1, 1, 1]: " + nn.predict(new double[]{0, 0, 1, 0, 0, 1, 1, 1})); System.out.println("Prediction for [0, 0, 1, 0, 1, 0, 0, 0]: " + nn.predict(new double[]{0, 0, 1, 0, 1, 0, 0, 0})); System.out.println("Prediction for [0, 0, 1, 0, 1, 0, 0, 1]: " + nn.predict(new double[]{0, 0, 1, 0, 1, 0, 0, 1})); System.out.println("Prediction for [0, 0, 1, 0, 1, 0, 1, 0]: " + nn.predict(new double[]{0, 0, 1, 0, 1, 0, 1, 0})); System.out.println("Prediction for [0, 0, 1, 0, 1, 0, 1, 1]: " + nn.predict(new double[]{0, 0, 1, 0, 1, 0, 1, 1})); System.out.println("Prediction for [0, 0, 1, 0, 1, 1, 0, 0]: " + nn.predict(new double[]{0, 0, 1, 0, 1, 1, 0, 0})); System.out.println("Prediction for [0, 0, 1, 0, 1, 1, 0, 1]: " + nn.predict(new double[]{0, 0, 1, 0, 1, 1, 0, 1})); System.out.println("Prediction for [0, 0, 1, 0, 1, 1, 1, 0]: " + nn.predict(new double[]{0, 0, 1, 0, 1, 1, 1, 0})); System.out.println("Prediction for [0, 0, 1, 0, 1, 1, 1, 1]: " + nn.predict(new double[]{0, 0, 1, 0, 1, 1, 1, 1})); System.out.println("Prediction for [0, 0, 1, 1, 0, 0, 0, 0]: " + nn.predict(new double[]{0, 0, 1, 1, 0, 0, 0, 0})); System.out.println("Prediction for [0, 0, 1, 1, 0, 0, 0, 1]: " + nn.predict(new double[]{0, 0, 1, 1, 0, 0, 0, 1})); System.out.println("Prediction for [0, 0, 1, 1, 0, 0, 1, 0]: " + nn.predict(new double[]{0, 0, 1, 1, 0, 0, 1, 0})); System.out.println("Prediction for [0, 0, 1, 1, 0, 0, 1, 1]: " + nn.predict(new double[]{0, 0, 1, 1, 0, 0, 1, 1})); System.out.println("Prediction for [0, 0, 1, 1, 0, 1, 0, 0]: " + nn.predict(new double[]{0, 0, 1, 1, 0, 1, 0, 0})); System.out.println("Prediction for [0, 0, 1, 1, 0, 1, 0, 1]: " + nn.predict(new double[]{0, 0, 1, 1, 0, 1, 0, 1})); System.out.println("Prediction for [0, 0, 1, 1, 0, 1, 1, 0]: " + nn.predict(new double[]{0, 0, 1, 1, 0, 1, 1, 0})); System.out.println("Prediction for [0, 0, 1, 1, 0, 1, 1, 1]: " + nn.predict(new double[]{0, 0, 1, 1, 0, 1, 1, 1})); System.out.println("Prediction for [0, 0, 1, 1, 1, 0, 0, 0]: " + nn.predict(new double[]{0, 0, 1, 1, 1, 0, 0, 0})); System.out.println("Prediction for [0, 0, 1, 1, 1, 0, 0, 1]: " + nn.predict(new double[]{0, 0, 1, 1, 1, 0, 0, 1})); System.out.println("Prediction for [0, 0, 1, 1, 1, 0, 1, 0]: " + nn.predict(new double[]{0, 0, 1, 1, 1, 0, 1, 0})); System.out.println("Prediction for [0, 0, 1, 1, 1, 0, 1, 1]: " + nn.predict(new double[]{0, 0, 1, 1, 1, 0, 1, 1})); System.out.println("Prediction for [0, 0, 1, 1, 1, 1, 0, 0]: " + nn.predict(new double[]{0, 0, 1, 1, 1, 1, 0, 0})); System.out.println("Prediction for [0, 0, 1, 1, 1, 1, 0, 1]: " + nn.predict(new double[]{0, 0, 1, 1, 1, 1, 0, 1})); System.out.println("Prediction for [0, 0, 1, 1, 1, 1, 1, 0]: " + nn.predict(new double[]{0, 0, 1, 1, 1, 1, 1, 0})); System.out.println("Prediction for [0, 0, 1, 1, 1, 1, 1, 1]: " + nn.predict(new double[]{0, 0, 1, 1, 1, 1, 1, 1})); System.out.println("Prediction for [0, 1, 0, 0, 0, 0, 0, 0]: " + nn.predict(new double[]{0, 1, 0, 0, 0, 0, 0, 0})); System.out.println("Prediction for [0, 1, 0, 0, 0, 0, 0, 1]: " + nn.predict(new double[]{0, 1, 0, 0, 0, 0, 0, 1})); System.out.println("Prediction for [0, 1, 0, 0, 0, 0, 1, 0]: " + nn.predict(new double[]{0, 1, 0, 0, 0, 0, 1, 0})); System.out.println("Prediction for [0, 1, 0, 0, 0, 0, 1, 1]: " + nn.predict(new double[]{0, 1, 0, 0, 0, 0, 1, 1})); System.out.println("Prediction for [0, 1, 0, 0, 0, 1, 0, 0]: " + nn.predict(new double[]{0, 1, 0, 0, 0, 1, 0, 0})); System.out.println("Prediction for [0, 1, 0, 0, 0, 1, 0, 1]: " + nn.predict(new double[]{0, 1, 0, 0, 0, 1, 0, 1})); System.out.println("Prediction for [0, 1, 0, 0, 0, 1, 1, 0]: " + nn.predict(new double[]{0, 1, 0, 0, 0, 1, 1, 0})); System.out.println("Prediction for [0, 1, 0, 0, 0, 1, 1, 1]: " + nn.predict(new double[]{0, 1, 0, 0, 0, 1, 1, 1})); System.out.println("Prediction for [0, 1, 0, 0, 1, 0, 0, 0]: " + nn.predict(new double[]{0, 1, 0, 0, 1, 0, 0, 0})); System.out.println("Prediction for [0, 1, 0, 0, 1, 0, 0, 1]: " + nn.predict(new double[]{0, 1, 0, 0, 1, 0, 0, 1})); System.out.println("Prediction for [0, 1, 0, 0, 1, 0, 1, 0]: " + nn.predict(new double[]{0, 1, 0, 0, 1, 0, 1, 0})); System.out.println("Prediction for [0, 1, 0, 0, 1, 0, 1, 1]: " + nn.predict(new double[]{0, 1, 0, 0, 1, 0, 1, 1})); System.out.println("Prediction for [0, 1, 0, 0, 1, 1, 0, 0]: " + nn.predict(new double[]{0, 1, 0, 0, 1, 1, 0, 0})); System.out.println("Prediction for [0, 1, 0, 0, 1, 1, 0, 1]: " + nn.predict(new double[]{0, 1, 0, 0, 1, 1, 0, 1})); System.out.println("Prediction for [0, 1, 0, 0, 1, 1, 1, 0]: " + nn.predict(new double[]{0, 1, 0, 0, 1, 1, 1, 0})); System.out.println("Prediction for [0, 1, 0, 0, 1, 1, 1, 1]: " + nn.predict(new double[]{0, 1, 0, 0, 1, 1, 1, 1})); System.out.println("Prediction for [0, 1, 0, 1, 0, 0, 0, 0]: " + nn.predict(new double[]{0, 1, 0, 1, 0, 0, 0, 0})); System.out.println("Prediction for [0, 1, 0, 1, 0, 0, 0, 1]: " + nn.predict(new double[]{0, 1, 0, 1, 0, 0, 0, 1})); System.out.println("Prediction for [0, 1, 0, 1, 0, 0, 1, 0]: " + nn.predict(new double[]{0, 1, 0, 1, 0, 0, 1, 0})); System.out.println("Prediction for [0, 1, 0, 1, 0, 0, 1, 1]: " + nn.predict(new double[]{0, 1, 0, 1, 0, 0, 1, 1})); System.out.println("Prediction for [0, 1, 0, 1, 0, 1, 0, 0]: " + nn.predict(new double[]{0, 1, 0, 1, 0, 1, 0, 0})); System.out.println("Prediction for [0, 1, 0, 1, 0, 1, 0, 1]: " + nn.predict(new double[]{0, 1, 0, 1, 0, 1, 0, 1})); System.out.println("Prediction for [0, 1, 0, 1, 0, 1, 1, 0]: " + nn.predict(new double[]{0, 1, 0, 1, 0, 1, 1, 0})); System.out.println("Prediction for [0, 1, 0, 1, 0, 1, 1, 1]: " + nn.predict(new double[]{0, 1, 0, 1, 0, 1, 1, 1})); System.out.println("Prediction for [0, 1, 0, 1, 1, 0, 0, 0]: " + nn.predict(new double[]{0, 1, 0, 1, 1, 0, 0, 0})); System.out.println("Prediction for [0, 1, 0, 1, 1, 0, 0, 1]: " + nn.predict(new double[]{0, 1, 0, 1, 1, 0, 0, 1})); System.out.println("Prediction for [0, 1, 0, 1, 1, 0, 1, 0]: " + nn.predict(new double[]{0, 1, 0, 1, 1, 0, 1, 0})); System.out.println("Prediction for [0, 1, 0, 1, 1, 0, 1, 1]: " + nn.predict(new double[]{0, 1, 0, 1, 1, 0, 1, 1})); System.out.println("Prediction for [0, 1, 0, 1, 1, 1, 0, 0]: " + nn.predict(new double[]{0, 1, 0, 1, 1, 1, 0, 0})); System.out.println("Prediction for [0, 1, 0, 1, 1, 1, 0, 1]: " + nn.predict(new double[]{0, 1, 0, 1, 1, 1, 0, 1})); System.out.println("Prediction for [0, 1, 0, 1, 1, 1, 1, 0]: " + nn.predict(new double[]{0, 1, 0, 1, 1, 1, 1, 0})); System.out.println("Prediction for [0, 1, 0, 1, 1, 1, 1, 1]: " + nn.predict(new double[]{0, 1, 0, 1, 1, 1, 1, 1})); System.out.println("Prediction for [0, 1, 1, 0, 0, 0, 0, 0]: " + nn.predict(new double[]{0, 1, 1, 0, 0, 0, 0, 0})); System.out.println("Prediction for [0, 1, 1, 0, 0, 0, 0, 1]: " + nn.predict(new double[]{0, 1, 1, 0, 0, 0, 0, 1})); System.out.println("Prediction for [0, 1, 1, 0, 0, 0, 1, 0]: " + nn.predict(new double[]{0, 1, 1, 0, 0, 0, 1, 0})); System.out.println("Prediction for [0, 1, 1, 0, 0, 0, 1, 1]: " + nn.predict(new double[]{0, 1, 1, 0, 0, 0, 1, 1})); System.out.println("Prediction for [0, 1, 1, 0, 0, 1, 0, 0]: " + nn.predict(new double[]{0, 1, 1, 0, 0, 1, 0, 0})); System.out.println("Prediction for [0, 1, 1, 0, 0, 1, 0, 1]: " + nn.predict(new double[]{0, 1, 1, 0, 0, 1, 0, 1})); System.out.println("Prediction for [0, 1, 1, 0, 0, 1, 1, 0]: " + nn.predict(new double[]{0, 1, 1, 0, 0, 1, 1, 0})); System.out.println("Prediction for [0, 1, 1, 0, 0, 1, 1, 1]: " + nn.predict(new double[]{0, 1, 1, 0, 0, 1, 1, 1})); System.out.println("Prediction for [0, 1, 1, 0, 1, 0, 0, 0]: " + nn.predict(new double[]{0, 1, 1, 0, 1, 0, 0, 0})); System.out.println("Prediction for [0, 1, 1, 0, 1, 0, 0, 1]: " + nn.predict(new double[]{0, 1, 1, 0, 1, 0, 0, 1})); System.out.println("Prediction for [0, 1, 1, 0, 1, 0, 1, 0]: " + nn.predict(new double[]{0, 1, 1, 0, 1, 0, 1, 0})); System.out.println("Prediction for [0, 1, 1, 0, 1, 0, 1, 1]: " + nn.predict(new double[]{0, 1, 1, 0, 1, 0, 1, 1})); System.out.println("Prediction for [0, 1, 1, 0, 1, 1, 0, 0]: " + nn.predict(new double[]{0, 1, 1, 0, 1, 1, 0, 0})); System.out.println("Prediction for [0, 1, 1, 0, 1, 1, 0, 1]: " + nn.predict(new double[]{0, 1, 1, 0, 1, 1, 0, 1})); System.out.println("Prediction for [0, 1, 1, 0, 1, 1, 1, 0]: " + nn.predict(new double[]{0, 1, 1, 0, 1, 1, 1, 0})); System.out.println("Prediction for [0, 1, 1, 0, 1, 1, 1, 1]: " + nn.predict(new double[]{0, 1, 1, 0, 1, 1, 1, 1})); System.out.println("Prediction for [0, 1, 1, 1, 0, 0, 0, 0]: " + nn.predict(new double[]{0, 1, 1, 1, 0, 0, 0, 0})); System.out.println("Prediction for [0, 1, 1, 1, 0, 0, 0, 1]: " + nn.predict(new double[]{0, 1, 1, 1, 0, 0, 0, 1})); System.out.println("Prediction for [0, 1, 1, 1, 0, 0, 1, 0]: " + nn.predict(new double[]{0, 1, 1, 1, 0, 0, 1, 0})); System.out.println("Prediction for [0, 1, 1, 1, 0, 0, 1, 1]: " + nn.predict(new double[]{0, 1, 1, 1, 0, 0, 1, 1})); System.out.println("Prediction for [0, 1, 1, 1, 0, 1, 0, 0]: " + nn.predict(new double[]{0, 1, 1, 1, 0, 1, 0, 0})); System.out.println("Prediction for [0, 1, 1, 1, 0, 1, 0, 1]: " + nn.predict(new double[]{0, 1, 1, 1, 0, 1, 0, 1})); System.out.println("Prediction for [0, 1, 1, 1, 0, 1, 1, 0]: " + nn.predict(new double[]{0, 1, 1, 1, 0, 1, 1, 0})); System.out.println("Prediction for [0, 1, 1, 1, 0, 1, 1, 1]: " + nn.predict(new double[]{0, 1, 1, 1, 0, 1, 1, 1})); System.out.println("Prediction for [0, 1, 1, 1, 1, 0, 0, 0]: " + nn.predict(new double[]{0, 1, 1, 1, 1, 0, 0, 0})); System.out.println("Prediction for [0, 1, 1, 1, 1, 0, 0, 1]: " + nn.predict(new double[]{0, 1, 1, 1, 1, 0, 0, 1})); System.out.println("Prediction for [0, 1, 1, 1, 1, 0, 1, 0]: " + nn.predict(new double[]{0, 1, 1, 1, 1, 0, 1, 0})); System.out.println("Prediction for [0, 1, 1, 1, 1, 0, 1, 1]: " + nn.predict(new double[]{0, 1, 1, 1, 1, 0, 1, 1})); System.out.println("Prediction for [0, 1, 1, 1, 1, 1, 0, 0]: " + nn.predict(new double[]{0, 1, 1, 1, 1, 1, 0, 0})); System.out.println("Prediction for [0, 1, 1, 1, 1, 1, 0, 1]: " + nn.predict(new double[]{0, 1, 1, 1, 1, 1, 0, 1})); System.out.println("Prediction for [0, 1, 1, 1, 1, 1, 1, 0]: " + nn.predict(new double[]{0, 1, 1, 1, 1, 1, 1, 0})); System.out.println("Prediction for [0, 1, 1, 1, 1, 1, 1, 1]: " + nn.predict(new double[]{0, 1, 1, 1, 1, 1, 1, 1})); System.out.println("Prediction for [1, 0, 0, 0, 0, 0, 0, 0]: " + nn.predict(new double[]{1, 0, 0, 0, 0, 0, 0, 0})); System.out.println("Prediction for [1, 0, 0, 0, 0, 0, 0, 1]: " + nn.predict(new double[]{1, 0, 0, 0, 0, 0, 0, 1})); System.out.println("Prediction for [1, 0, 0, 0, 0, 0, 1, 0]: " + nn.predict(new double[]{1, 0, 0, 0, 0, 0, 1, 0})); System.out.println("Prediction for [1, 0, 0, 0, 0, 0, 1, 1]: " + nn.predict(new double[]{1, 0, 0, 0, 0, 0, 1, 1})); System.out.println("Prediction for [1, 0, 0, 0, 0, 1, 0, 0]: " + nn.predict(new double[]{1, 0, 0, 0, 0, 1, 0, 0})); System.out.println("Prediction for [1, 0, 0, 0, 0, 1, 0, 1]: " + nn.predict(new double[]{1, 0, 0, 0, 0, 1, 0, 1})); System.out.println("Prediction for [1, 0, 0, 0, 0, 1, 1, 0]: " + nn.predict(new double[]{1, 0, 0, 0, 0, 1, 1, 0})); System.out.println("Prediction for [1, 0, 0, 0, 0, 1, 1, 1]: " + nn.predict(new double[]{1, 0, 0, 0, 0, 1, 1, 1})); System.out.println("Prediction for [1, 0, 0, 0, 1, 0, 0, 0]: " + nn.predict(new double[]{1, 0, 0, 0, 1, 0, 0, 0})); System.out.println("Prediction for [1, 0, 0, 0, 1, 0, 0, 1]: " + nn.predict(new double[]{1, 0, 0, 0, 1, 0, 0, 1})); System.out.println("Prediction for [1, 0, 0, 0, 1, 0, 1, 0]: " + nn.predict(new double[]{1, 0, 0, 0, 1, 0, 1, 0})); System.out.println("Prediction for [1, 0, 0, 0, 1, 0, 1, 1]: " + nn.predict(new double[]{1, 0, 0, 0, 1, 0, 1, 1})); System.out.println("Prediction for [1, 0, 0, 0, 1, 1, 0, 0]: " + nn.predict(new double[]{1, 0, 0, 0, 1, 1, 0, 0})); System.out.println("Prediction for [1, 0, 0, 0, 1, 1, 0, 1]: " + nn.predict(new double[]{1, 0, 0, 0, 1, 1, 0, 1})); System.out.println("Prediction for [1, 0, 0, 0, 1, 1, 1, 0]: " + nn.predict(new double[]{1, 0, 0, 0, 1, 1, 1, 0})); System.out.println("Prediction for [1, 0, 0, 0, 1, 1, 1, 1]: " + nn.predict(new double[]{1, 0, 0, 0, 1, 1, 1, 1})); System.out.println("Prediction for [1, 0, 0, 1, 0, 0, 0, 0]: " + nn.predict(new double[]{1, 0, 0, 1, 0, 0, 0, 0})); System.out.println("Prediction for [1, 0, 0, 1, 0, 0, 0, 1]: " + nn.predict(new double[]{1, 0, 0, 1, 0, 0, 0, 1})); System.out.println("Prediction for [1, 0, 0, 1, 0, 0, 1, 0]: " + nn.predict(new double[]{1, 0, 0, 1, 0, 0, 1, 0})); System.out.println("Prediction for [1, 0, 0, 1, 0, 0, 1, 1]: " + nn.predict(new double[]{1, 0, 0, 1, 0, 0, 1, 1})); System.out.println("Prediction for [1, 0, 0, 1, 0, 1, 0, 0]: " + nn.predict(new double[]{1, 0, 0, 1, 0, 1, 0, 0})); System.out.println("Prediction for [1, 0, 0, 1, 0, 1, 0, 1]: " + nn.predict(new double[]{1, 0, 0, 1, 0, 1, 0, 1})); System.out.println("Prediction for [1, 0, 0, 1, 0, 1, 1, 0]: " + nn.predict(new double[]{1, 0, 0, 1, 0, 1, 1, 0})); System.out.println("Prediction for [1, 0, 0, 1, 0, 1, 1, 1]: " + nn.predict(new double[]{1, 0, 0, 1, 0, 1, 1, 1})); System.out.println("Prediction for [1, 0, 0, 1, 1, 0, 0, 0]: " + nn.predict(new double[]{1, 0, 0, 1, 1, 0, 0, 0})); System.out.println("Prediction for [1, 0, 0, 1, 1, 0, 0, 1]: " + nn.predict(new double[]{1, 0, 0, 1, 1, 0, 0, 1})); System.out.println("Prediction for [1, 0, 0, 1, 1, 0, 1, 0]: " + nn.predict(new double[]{1, 0, 0, 1, 1, 0, 1, 0})); System.out.println("Prediction for [1, 0, 0, 1, 1, 0, 1, 1]: " + nn.predict(new double[]{1, 0, 0, 1, 1, 0, 1, 1})); System.out.println("Prediction for [1, 0, 0, 1, 1, 1, 0, 0]: " + nn.predict(new double[]{1, 0, 0, 1, 1, 1, 0, 0})); System.out.println("Prediction for [1, 0, 0, 1, 1, 1, 0, 1]: " + nn.predict(new double[]{1, 0, 0, 1, 1, 1, 0, 1})); System.out.println("Prediction for [1, 0, 0, 1, 1, 1, 1, 0]: " + nn.predict(new double[]{1, 0, 0, 1, 1, 1, 1, 0})); System.out.println("Prediction for [1, 0, 0, 1, 1, 1, 1, 1]: " + nn.predict(new double[]{1, 0, 0, 1, 1, 1, 1, 1})); System.out.println("Prediction for [1, 0, 1, 0, 0, 0, 0, 0]: " + nn.predict(new double[]{1, 0, 1, 0, 0, 0, 0, 0})); System.out.println("Prediction for [1, 0, 1, 0, 0, 0, 0, 1]: " + nn.predict(new double[]{1, 0, 1, 0, 0, 0, 0, 1})); System.out.println("Prediction for [1, 0, 1, 0, 0, 0, 1, 0]: " + nn.predict(new double[]{1, 0, 1, 0, 0, 0, 1, 0})); System.out.println("Prediction for [1, 0, 1, 0, 0, 0, 1, 1]: " + nn.predict(new double[]{1, 0, 1, 0, 0, 0, 1, 1})); System.out.println("Prediction for [1, 0, 1, 0, 0, 1, 0, 0]: " + nn.predict(new double[]{1, 0, 1, 0, 0, 1, 0, 0})); System.out.println("Prediction for [1, 0, 1, 0, 0, 1, 0, 1]: " + nn.predict(new double[]{1, 0, 1, 0, 0, 1, 0, 1})); System.out.println("Prediction for [1, 0, 1, 0, 0, 1, 1, 0]: " + nn.predict(new double[]{1, 0, 1, 0, 0, 1, 1, 0})); System.out.println("Prediction for [1, 0, 1, 0, 0, 1, 1, 1]: " + nn.predict(new double[]{1, 0, 1, 0, 0, 1, 1, 1})); System.out.println("Prediction for [1, 0, 1, 0, 1, 0, 0, 0]: " + nn.predict(new double[]{1, 0, 1, 0, 1, 0, 0, 0})); System.out.println("Prediction for [1, 0, 1, 0, 1, 0, 0, 1]: " + nn.predict(new double[]{1, 0, 1, 0, 1, 0, 0, 1})); System.out.println("Prediction for [1, 0, 1, 0, 1, 0, 1, 0]: " + nn.predict(new double[]{1, 0, 1, 0, 1, 0, 1, 0})); System.out.println("Prediction for [1, 0, 1, 0, 1, 0, 1, 1]: " + nn.predict(new double[]{1, 0, 1, 0, 1, 0, 1, 1})); System.out.println("Prediction for [1, 0, 1, 0, 1, 1, 0, 0]: " + nn.predict(new double[]{1, 0, 1, 0, 1, 1, 0, 0})); System.out.println("Prediction for [1, 0, 1, 0, 1, 1, 0, 1]: " + nn.predict(new double[]{1, 0, 1, 0, 1, 1, 0, 1})); System.out.println("Prediction for [1, 0, 1, 0, 1, 1, 1, 0]: " + nn.predict(new double[]{1, 0, 1, 0, 1, 1, 1, 0})); System.out.println("Prediction for [1, 0, 1, 0, 1, 1, 1, 1]: " + nn.predict(new double[]{1, 0, 1, 0, 1, 1, 1, 1})); System.out.println("Prediction for [1, 0, 1, 1, 0, 0, 0, 0]: " + nn.predict(new double[]{1, 0, 1, 1, 0, 0, 0, 0})); System.out.println("Prediction for [1, 0, 1, 1, 0, 0, 0, 1]: " + nn.predict(new double[]{1, 0, 1, 1, 0, 0, 0, 1})); System.out.println("Prediction for [1, 0, 1, 1, 0, 0, 1, 0]: " + nn.predict(new double[]{1, 0, 1, 1, 0, 0, 1, 0})); System.out.println("Prediction for [1, 0, 1, 1, 0, 0, 1, 1]: " + nn.predict(new double[]{1, 0, 1, 1, 0, 0, 1, 1})); System.out.println("Prediction for [1, 0, 1, 1, 0, 1, 0, 0]: " + nn.predict(new double[]{1, 0, 1, 1, 0, 1, 0, 0})); System.out.println("Prediction for [1, 0, 1, 1, 0, 1, 0, 1]: " + nn.predict(new double[]{1, 0, 1, 1, 0, 1, 0, 1})); System.out.println("Prediction for [1, 0, 1, 1, 0, 1, 1, 0]: " + nn.predict(new double[]{1, 0, 1, 1, 0, 1, 1, 0})); System.out.println("Prediction for [1, 0, 1, 1, 0, 1, 1, 1]: " + nn.predict(new double[]{1, 0, 1, 1, 0, 1, 1, 1})); System.out.println("Prediction for [1, 0, 1, 1, 1, 0, 0, 0]: " + nn.predict(new double[]{1, 0, 1, 1, 1, 0, 0, 0})); System.out.println("Prediction for [1, 0, 1, 1, 1, 0, 0, 1]: " + nn.predict(new double[]{1, 0, 1, 1, 1, 0, 0, 1})); System.out.println("Prediction for [1, 0, 1, 1, 1, 0, 1, 0]: " + nn.predict(new double[]{1, 0, 1, 1, 1, 0, 1, 0})); System.out.println("Prediction for [1, 0, 1, 1, 1, 0, 1, 1]: " + nn.predict(new double[]{1, 0, 1, 1, 1, 0, 1, 1})); System.out.println("Prediction for [1, 0, 1, 1, 1, 1, 0, 0]: " + nn.predict(new double[]{1, 0, 1, 1, 1, 1, 0, 0})); System.out.println("Prediction for [1, 0, 1, 1, 1, 1, 0, 1]: " + nn.predict(new double[]{1, 0, 1, 1, 1, 1, 0, 1})); System.out.println("Prediction for [1, 0, 1, 1, 1, 1, 1, 0]: " + nn.predict(new double[]{1, 0, 1, 1, 1, 1, 1, 0})); System.out.println("Prediction for [1, 0, 1, 1, 1, 1, 1, 1]: " + nn.predict(new double[]{1, 0, 1, 1, 1, 1, 1, 1})); System.out.println("Prediction for [1, 1, 0, 0, 0, 0, 0, 0]: " + nn.predict(new double[]{1, 1, 0, 0, 0, 0, 0, 0})); System.out.println("Prediction for [1, 1, 0, 0, 0, 0, 0, 1]: " + nn.predict(new double[]{1, 1, 0, 0, 0, 0, 0, 1})); System.out.println("Prediction for [1, 1, 0, 0, 0, 0, 1, 0]: " + nn.predict(new double[]{1, 1, 0, 0, 0, 0, 1, 0})); System.out.println("Prediction for [1, 1, 0, 0, 0, 0, 1, 1]: " + nn.predict(new double[]{1, 1, 0, 0, 0, 0, 1, 1})); System.out.println("Prediction for [1, 1, 0, 0, 0, 1, 0, 0]: " + nn.predict(new double[]{1, 1, 0, 0, 0, 1, 0, 0})); System.out.println("Prediction for [1, 1, 0, 0, 0, 1, 0, 1]: " + nn.predict(new double[]{1, 1, 0, 0, 0, 1, 0, 1})); System.out.println("Prediction for [1, 1, 0, 0, 0, 1, 1, 0]: " + nn.predict(new double[]{1, 1, 0, 0, 0, 1, 1, 0})); System.out.println("Prediction for [1, 1, 0, 0, 0, 1, 1, 1]: " + nn.predict(new double[]{1, 1, 0, 0, 0, 1, 1, 1})); System.out.println("Prediction for [1, 1, 0, 0, 1, 0, 0, 0]: " + nn.predict(new double[]{1, 1, 0, 0, 1, 0, 0, 0})); System.out.println("Prediction for [1, 1, 0, 0, 1, 0, 0, 1]: " + nn.predict(new double[]{1, 1, 0, 0, 1, 0, 0, 1})); System.out.println("Prediction for [1, 1, 0, 0, 1, 0, 1, 0]: " + nn.predict(new double[]{1, 1, 0, 0, 1, 0, 1, 0})); System.out.println("Prediction for [1, 1, 0, 0, 1, 0, 1, 1]: " + nn.predict(new double[]{1, 1, 0, 0, 1, 0, 1, 1})); System.out.println("Prediction for [1, 1, 0, 0, 1, 1, 0, 0]: " + nn.predict(new double[]{1, 1, 0, 0, 1, 1, 0, 0})); System.out.println("Prediction for [1, 1, 0, 0, 1, 1, 0, 1]: " + nn.predict(new double[]{1, 1, 0, 0, 1, 1, 0, 1})); System.out.println("Prediction for [1, 1, 0, 0, 1, 1, 1, 0]: " + nn.predict(new double[]{1, 1, 0, 0, 1, 1, 1, 0})); System.out.println("Prediction for [1, 1, 0, 0, 1, 1, 1, 1]: " + nn.predict(new double[]{1, 1, 0, 0, 1, 1, 1, 1})); System.out.println("Prediction for [1, 1, 0, 1, 0, 0, 0, 0]: " + nn.predict(new double[]{1, 1, 0, 1, 0, 0, 0, 0})); System.out.println("Prediction for [1, 1, 0, 1, 0, 0, 0, 1]: " + nn.predict(new double[]{1, 1, 0, 1, 0, 0, 0, 1})); System.out.println("Prediction for [1, 1, 0, 1, 0, 0, 1, 0]: " + nn.predict(new double[]{1, 1, 0, 1, 0, 0, 1, 0})); System.out.println("Prediction for [1, 1, 0, 1, 0, 0, 1, 1]: " + nn.predict(new double[]{1, 1, 0, 1, 0, 0, 1, 1})); System.out.println("Prediction for [1, 1, 0, 1, 0, 1, 0, 0]: " + nn.predict(new double[]{1, 1, 0, 1, 0, 1, 0, 0})); System.out.println("Prediction for [1, 1, 0, 1, 0, 1, 0, 1]: " + nn.predict(new double[]{1, 1, 0, 1, 0, 1, 0, 1})); System.out.println("Prediction for [1, 1, 0, 1, 0, 1, 1, 0]: " + nn.predict(new double[]{1, 1, 0, 1, 0, 1, 1, 0})); System.out.println("Prediction for [1, 1, 0, 1, 0, 1, 1, 1]: " + nn.predict(new double[]{1, 1, 0, 1, 0, 1, 1, 1})); System.out.println("Prediction for [1, 1, 0, 1, 1, 0, 0, 0]: " + nn.predict(new double[]{1, 1, 0, 1, 1, 0, 0, 0})); System.out.println("Prediction for [1, 1, 0, 1, 1, 0, 0, 1]: " + nn.predict(new double[]{1, 1, 0, 1, 1, 0, 0, 1})); System.out.println("Prediction for [1, 1, 0, 1, 1, 0, 1, 0]: " + nn.predict(new double[]{1, 1, 0, 1, 1, 0, 1, 0})); System.out.println("Prediction for [1, 1, 0, 1, 1, 0, 1, 1]: " + nn.predict(new double[]{1, 1, 0, 1, 1, 0, 1, 1})); System.out.println("Prediction for [1, 1, 0, 1, 1, 1, 0, 0]: " + nn.predict(new double[]{1, 1, 0, 1, 1, 1, 0, 0})); System.out.println("Prediction for [1, 1, 0, 1, 1, 1, 0, 1]: " + nn.predict(new double[]{1, 1, 0, 1, 1, 1, 0, 1})); System.out.println("Prediction for [1, 1, 0, 1, 1, 1, 1, 0]: " + nn.predict(new double[]{1, 1, 0, 1, 1, 1, 1, 0})); System.out.println("Prediction for [1, 1, 0, 1, 1, 1, 1, 1]: " + nn.predict(new double[]{1, 1, 0, 1, 1, 1, 1, 1})); System.out.println("Prediction for [1, 1, 1, 0, 0, 0, 0, 0]: " + nn.predict(new double[]{1, 1, 1, 0, 0, 0, 0, 0})); System.out.println("Prediction for [1, 1, 1, 0, 0, 0, 0, 1]: " + nn.predict(new double[]{1, 1, 1, 0, 0, 0, 0, 1})); System.out.println("Prediction for [1, 1, 1, 0, 0, 0, 1, 0]: " + nn.predict(new double[]{1, 1, 1, 0, 0, 0, 1, 0})); System.out.println("Prediction for [1, 1, 1, 0, 0, 0, 1, 1]: " + nn.predict(new double[]{1, 1, 1, 0, 0, 0, 1, 1})); System.out.println("Prediction for [1, 1, 1, 0, 0, 1, 0, 0]: " + nn.predict(new double[]{1, 1, 1, 0, 0, 1, 0, 0})); System.out.println("Prediction for [1, 1, 1, 0, 0, 1, 0, 1]: " + nn.predict(new double[]{1, 1, 1, 0, 0, 1, 0, 1})); System.out.println("Prediction for [1, 1, 1, 0, 0, 1, 1, 0]: " + nn.predict(new double[]{1, 1, 1, 0, 0, 1, 1, 0})); System.out.println("Prediction for [1, 1, 1, 0, 0, 1, 1, 1]: " + nn.predict(new double[]{1, 1, 1, 0, 0, 1, 1, 1})); System.out.println("Prediction for [1, 1, 1, 0, 1, 0, 0, 0]: " + nn.predict(new double[]{1, 1, 1, 0, 1, 0, 0, 0})); System.out.println("Prediction for [1, 1, 1, 0, 1, 0, 0, 1]: " + nn.predict(new double[]{1, 1, 1, 0, 1, 0, 0, 1})); System.out.println("Prediction for [1, 1, 1, 0, 1, 0, 1, 0]: " + nn.predict(new double[]{1, 1, 1, 0, 1, 0, 1, 0})); System.out.println("Prediction for [1, 1, 1, 0, 1, 0, 1, 1]: " + nn.predict(new double[]{1, 1, 1, 0, 1, 0, 1, 1})); System.out.println("Prediction for [1, 1, 1, 0, 1, 1, 0, 0]: " + nn.predict(new double[]{1, 1, 1, 0, 1, 1, 0, 0})); System.out.println("Prediction for [1, 1, 1, 0, 1, 1, 0, 1]: " + nn.predict(new double[]{1, 1, 1, 0, 1, 1, 0, 1})); System.out.println("Prediction for [1, 1, 1, 0, 1, 1, 1, 0]: " + nn.predict(new double[]{1, 1, 1, 0, 1, 1, 1, 0})); System.out.println("Prediction for [1, 1, 1, 0, 1, 1, 1, 1]: " + nn.predict(new double[]{1, 1, 1, 0, 1, 1, 1, 1})); System.out.println("Prediction for [1, 1, 1, 1, 0, 0, 0, 0]: " + nn.predict(new double[]{1, 1, 1, 1, 0, 0, 0, 0})); System.out.println("Prediction for [1, 1, 1, 1, 0, 0, 0, 1]: " + nn.predict(new double[]{1, 1, 1, 1, 0, 0, 0, 1})); System.out.println("Prediction for [1, 1, 1, 1, 0, 0, 1, 0]: " + nn.predict(new double[]{1, 1, 1, 1, 0, 0, 1, 0})); System.out.println("Prediction for [1, 1, 1, 1, 0, 0, 1, 1]: " + nn.predict(new double[]{1, 1, 1, 1, 0, 0, 1, 1})); System.out.println("Prediction for [1, 1, 1, 1, 0, 1, 0, 0]: " + nn.predict(new double[]{1, 1, 1, 1, 0, 1, 0, 0})); System.out.println("Prediction for [1, 1, 1, 1, 0, 1, 0, 1]: " + nn.predict(new double[]{1, 1, 1, 1, 0, 1, 0, 1})); System.out.println("Prediction for [1, 1, 1, 1, 0, 1, 1, 0]: " + nn.predict(new double[]{1, 1, 1, 1, 0, 1, 1, 0})); System.out.println("Prediction for [1, 1, 1, 1, 0, 1, 1, 1]: " + nn.predict(new double[]{1, 1, 1, 1, 0, 1, 1, 1})); System.out.println("Prediction for [1, 1, 1, 1, 1, 0, 0, 0]: " + nn.predict(new double[]{1, 1, 1, 1, 1, 0, 0, 0})); System.out.println("Prediction for [1, 1, 1, 1, 1, 0, 0, 1]: " + nn.predict(new double[]{1, 1, 1, 1, 1, 0, 0, 1})); System.out.println("Prediction for [1, 1, 1, 1, 1, 0, 1, 0]: " + nn.predict(new double[]{1, 1, 1, 1, 1, 0, 1, 0})); System.out.println("Prediction for [1, 1, 1, 1, 1, 0, 1, 1]: " + nn.predict(new double[]{1, 1, 1, 1, 1, 0, 1, 1})); System.out.println("Prediction for [1, 1, 1, 1, 1, 1, 0, 0]: " + nn.predict(new double[]{1, 1, 1, 1, 1, 1, 0, 0})); System.out.println("Prediction for [1, 1, 1, 1, 1, 1, 0, 1]: " + nn.predict(new double[]{1, 1, 1, 1, 1, 1, 0, 1})); System.out.println("Prediction for [1, 1, 1, 1, 1, 1, 1, 0]: " + nn.predict(new double[]{1, 1, 1, 1, 1, 1, 1, 0})); System.out.println("Prediction for [1, 1, 1, 1, 1, 1, 1, 1]: " + nn.predict(new double[]{1, 1, 1, 1, 1, 1, 1, 1})); } } run: Epoch 10000. Mean error: 0.02287697440085921 Epoch 20000. Mean error: 0.014166625707716164 Epoch 30000. Mean error: 0.009129459849268452 Epoch 40000. Mean error: 0.006841828176043919 Epoch 50000. Mean error: 0.00567235761602261 Epoch 60000. Mean error: 0.004962131900172744 Epoch 70000. Mean error: 0.004497326734313791 Epoch 80000. Mean error: 0.004275845259380384 Epoch 90000. Mean error: 0.0041453052883488085 Epoch 100000. Mean error: 0.004062262123553563 Epoch 110000. Mean error: 0.004009026698502614 Epoch 120000. Mean error: 0.003968548498876892 Epoch 130000. Mean error: 0.003945200641862105 Epoch 140000. Mean error: 0.003930767972347983 Epoch 150000. Mean error: 0.00392177340097129 Epoch 160000. Mean error: 0.003916138888637087 Epoch 170000. Mean error: 0.003912588636981584 Epoch 180000. Mean error: 0.003910307713603723 Epoch 190000. Mean error: 0.003908885306420438 Epoch 200000. Mean error: 0.003907975041400942 Prediction for [0, 0, 0, 0, 0, 0, 0, 0]: 0.0 Prediction for [0, 0, 0, 0, 0, 0, 0, 1]: 1.0002396760102368 Prediction for [0, 0, 0, 0, 0, 0, 1, 0]: 0.0 Prediction for [0, 0, 0, 0, 0, 0, 1, 1]: 1.000073549804653 Prediction for [0, 0, 0, 0, 0, 1, 0, 0]: 0.0 Prediction for [0, 0, 0, 0, 0, 1, 0, 1]: 1.0001648629047235 Prediction for [0, 0, 0, 0, 0, 1, 1, 0]: 0.0 Prediction for [0, 0, 0, 0, 0, 1, 1, 1]: 0.9999256290123881 Prediction for [0, 0, 0, 0, 1, 0, 0, 0]: 0.0 Prediction for [0, 0, 0, 0, 1, 0, 0, 1]: 0.0 Prediction for [0, 0, 0, 0, 1, 0, 1, 0]: 0.0 Prediction for [0, 0, 0, 0, 1, 0, 1, 1]: 1.0001481342838092 Prediction for [0, 0, 0, 0, 1, 1, 0, 0]: 0.0 Prediction for [0, 0, 0, 0, 1, 1, 0, 1]: 0.9999877850696732 Prediction for [0, 0, 0, 0, 1, 1, 1, 0]: 0.0 Prediction for [0, 0, 0, 0, 1, 1, 1, 1]: 0.0 Prediction for [0, 0, 0, 1, 0, 0, 0, 0]: 0.0 Prediction for [0, 0, 0, 1, 0, 0, 0, 1]: 1.0000288093042053 Prediction for [0, 0, 0, 1, 0, 0, 1, 0]: 0.0 Prediction for [0, 0, 0, 1, 0, 0, 1, 1]: 0.9997639084790277 Prediction for [0, 0, 0, 1, 0, 1, 0, 0]: 0.0 Prediction for [0, 0, 0, 1, 0, 1, 0, 1]: 0.0 Prediction for [0, 0, 0, 1, 0, 1, 1, 0]: 0.0 Prediction for [0, 0, 0, 1, 0, 1, 1, 1]: 1.0001190831863198 Prediction for [0, 0, 0, 1, 1, 0, 0, 0]: 0.0 Prediction for [0, 0, 0, 1, 1, 0, 0, 1]: 0.0 Prediction for [0, 0, 0, 1, 1, 0, 1, 0]: 0.0 Prediction for [0, 0, 0, 1, 1, 0, 1, 1]: 0.0 Prediction for [0, 0, 0, 1, 1, 1, 0, 0]: 0.0 Prediction for [0, 0, 0, 1, 1, 1, 0, 1]: 0.9999319677714649 Prediction for [0, 0, 0, 1, 1, 1, 1, 0]: 0.0 Prediction for [0, 0, 0, 1, 1, 1, 1, 1]: 1.0003404389083057 Prediction for [0, 0, 1, 0, 0, 0, 0, 0]: 0.0 Prediction for [0, 0, 1, 0, 0, 0, 0, 1]: 0.0 Prediction for [0, 0, 1, 0, 0, 0, 1, 0]: 0.0 Prediction for [0, 0, 1, 0, 0, 0, 1, 1]: 0.0 Prediction for [0, 0, 1, 0, 0, 1, 0, 0]: 0.0 Prediction for [0, 0, 1, 0, 0, 1, 0, 1]: 1.0000475454581501 Prediction for [0, 0, 1, 0, 0, 1, 1, 0]: 0.0 Prediction for [0, 0, 1, 0, 0, 1, 1, 1]: 0.0 Prediction for [0, 0, 1, 0, 1, 0, 0, 0]: 0.0 Prediction for [0, 0, 1, 0, 1, 0, 0, 1]: 0.9996586371051661 Prediction for [0, 0, 1, 0, 1, 0, 1, 0]: 0.0 Prediction for [0, 0, 1, 0, 1, 0, 1, 1]: 1.0000028179007723 Prediction for [0, 0, 1, 0, 1, 1, 0, 0]: 0.0 Prediction for [0, 0, 1, 0, 1, 1, 0, 1]: 0.0 Prediction for [0, 0, 1, 0, 1, 1, 1, 0]: 0.0 Prediction for [0, 0, 1, 0, 1, 1, 1, 1]: 0.9995298039153093 Prediction for [0, 0, 1, 1, 0, 0, 0, 0]: 0.0 Prediction for [0, 0, 1, 1, 0, 0, 0, 1]: 0.0 Prediction for [0, 0, 1, 1, 0, 0, 1, 0]: 0.0 Prediction for [0, 0, 1, 1, 0, 0, 1, 1]: 0.0 Prediction for [0, 0, 1, 1, 0, 1, 0, 0]: 0.0 Prediction for [0, 0, 1, 1, 0, 1, 0, 1]: 1.000053063623958 Prediction for [0, 0, 1, 1, 0, 1, 1, 0]: 0.0 Prediction for [0, 0, 1, 1, 0, 1, 1, 1]: 0.0 Prediction for [0, 0, 1, 1, 1, 0, 0, 0]: 0.0 Prediction for [0, 0, 1, 1, 1, 0, 0, 1]: 0.0 Prediction for [0, 0, 1, 1, 1, 0, 1, 0]: 0.0 Prediction for [0, 0, 1, 1, 1, 0, 1, 1]: 0.9994418900661293 Prediction for [0, 0, 1, 1, 1, 1, 0, 0]: 0.0 Prediction for [0, 0, 1, 1, 1, 1, 0, 1]: 0.9985201195558622 Prediction for [0, 0, 1, 1, 1, 1, 1, 0]: 0.0 Prediction for [0, 0, 1, 1, 1, 1, 1, 1]: 8.29103443267698E-4 Prediction for [0, 1, 0, 0, 0, 0, 0, 0]: 0.0 Prediction for [0, 1, 0, 0, 0, 0, 0, 1]: 0.0 Prediction for [0, 1, 0, 0, 0, 0, 1, 0]: 0.0 Prediction for [0, 1, 0, 0, 0, 0, 1, 1]: 0.9999782810841431 Prediction for [0, 1, 0, 0, 0, 1, 0, 0]: 0.0 Prediction for [0, 1, 0, 0, 0, 1, 0, 1]: 0.0 Prediction for [0, 1, 0, 0, 0, 1, 1, 0]: 0.0 Prediction for [0, 1, 0, 0, 0, 1, 1, 1]: 0.9999056375664708 Prediction for [0, 1, 0, 0, 1, 0, 0, 0]: 0.0 Prediction for [0, 1, 0, 0, 1, 0, 0, 1]: 0.9998720318399794 Prediction for [0, 1, 0, 0, 1, 0, 1, 0]: 0.0 Prediction for [0, 1, 0, 0, 1, 0, 1, 1]: 0.0 Prediction for [0, 1, 0, 0, 1, 1, 0, 0]: 0.0 Prediction for [0, 1, 0, 0, 1, 1, 0, 1]: 0.0 Prediction for [0, 1, 0, 0, 1, 1, 1, 0]: 0.0 Prediction for [0, 1, 0, 0, 1, 1, 1, 1]: 0.9985244522237924 Prediction for [0, 1, 0, 1, 0, 0, 0, 0]: 0.0 Prediction for [0, 1, 0, 1, 0, 0, 0, 1]: 0.0 Prediction for [0, 1, 0, 1, 0, 0, 1, 0]: 0.0 Prediction for [0, 1, 0, 1, 0, 0, 1, 1]: 0.999698882074032 Prediction for [0, 1, 0, 1, 0, 1, 0, 0]: 0.0 Prediction for [0, 1, 0, 1, 0, 1, 0, 1]: 0.0 Prediction for [0, 1, 0, 1, 0, 1, 1, 0]: 0.0 Prediction for [0, 1, 0, 1, 0, 1, 1, 1]: 0.0 Prediction for [0, 1, 0, 1, 1, 0, 0, 0]: 0.0 Prediction for [0, 1, 0, 1, 1, 0, 0, 1]: 0.9997755881672816 Prediction for [0, 1, 0, 1, 1, 0, 1, 0]: 0.0 Prediction for [0, 1, 0, 1, 1, 0, 1, 1]: 0.0 Prediction for [0, 1, 0, 1, 1, 1, 0, 0]: 0.0 Prediction for [0, 1, 0, 1, 1, 1, 0, 1]: 0.0 Prediction for [0, 1, 0, 1, 1, 1, 1, 0]: 0.0 Prediction for [0, 1, 0, 1, 1, 1, 1, 1]: 0.0 Prediction for [0, 1, 1, 0, 0, 0, 0, 0]: 0.0 Prediction for [0, 1, 1, 0, 0, 0, 0, 1]: 0.9991710505573721 Prediction for [0, 1, 1, 0, 0, 0, 1, 0]: 0.0 Prediction for [0, 1, 1, 0, 0, 0, 1, 1]: 0.0 Prediction for [0, 1, 1, 0, 0, 1, 0, 0]: 0.0 Prediction for [0, 1, 1, 0, 0, 1, 0, 1]: 1.0000549707847384 Prediction for [0, 1, 1, 0, 0, 1, 1, 0]: 0.0 Prediction for [0, 1, 1, 0, 0, 1, 1, 1]: 0.9912238113591538 Prediction for [0, 1, 1, 0, 1, 0, 0, 0]: 0.0 Prediction for [0, 1, 1, 0, 1, 0, 0, 1]: 8.873951351509035E-4 Prediction for [0, 1, 1, 0, 1, 0, 1, 0]: 0.0 Prediction for [0, 1, 1, 0, 1, 0, 1, 1]: 0.9989553071131994 Prediction for [0, 1, 1, 0, 1, 1, 0, 0]: 0.0 Prediction for [0, 1, 1, 0, 1, 1, 0, 1]: 0.9987057794724432 Prediction for [0, 1, 1, 0, 1, 1, 1, 0]: 0.0 Prediction for [0, 1, 1, 0, 1, 1, 1, 1]: 0.007308804190367724 Prediction for [0, 1, 1, 1, 0, 0, 0, 0]: 0.0 Prediction for [0, 1, 1, 1, 0, 0, 0, 1]: 0.999810972353874 Prediction for [0, 1, 1, 1, 0, 0, 1, 0]: 0.0 Prediction for [0, 1, 1, 1, 0, 0, 1, 1]: 0.0 Prediction for [0, 1, 1, 1, 0, 1, 0, 0]: 0.0 Prediction for [0, 1, 1, 1, 0, 1, 0, 1]: 0.0 Prediction for [0, 1, 1, 1, 0, 1, 1, 0]: 0.0 Prediction for [0, 1, 1, 1, 0, 1, 1, 1]: 0.0 Prediction for [0, 1, 1, 1, 1, 0, 0, 0]: 0.0 Prediction for [0, 1, 1, 1, 1, 0, 0, 1]: 0.0 Prediction for [0, 1, 1, 1, 1, 0, 1, 0]: 0.0 Prediction for [0, 1, 1, 1, 1, 0, 1, 1]: 0.0011432086006193387 Prediction for [0, 1, 1, 1, 1, 1, 0, 0]: 0.0 Prediction for [0, 1, 1, 1, 1, 1, 0, 1]: 0.0 Prediction for [0, 1, 1, 1, 1, 1, 1, 0]: 0.0 Prediction for [0, 1, 1, 1, 1, 1, 1, 1]: 0.9998262392016439 Prediction for [1, 0, 0, 0, 0, 0, 0, 0]: 0.0 Prediction for [1, 0, 0, 0, 0, 0, 0, 1]: 0.0 Prediction for [1, 0, 0, 0, 0, 0, 1, 0]: 0.0 Prediction for [1, 0, 0, 0, 0, 0, 1, 1]: 1.0002643177127801 Prediction for [1, 0, 0, 0, 0, 1, 0, 0]: 0.0 Prediction for [1, 0, 0, 0, 0, 1, 0, 1]: 0.0 Prediction for [1, 0, 0, 0, 0, 1, 1, 0]: 0.0 Prediction for [1, 0, 0, 0, 0, 1, 1, 1]: 2.9922117926517444E-5 Prediction for [1, 0, 0, 0, 1, 0, 0, 0]: 0.0 Prediction for [1, 0, 0, 0, 1, 0, 0, 1]: 1.0000109097269831 Prediction for [1, 0, 0, 0, 1, 0, 1, 0]: 0.0 Prediction for [1, 0, 0, 0, 1, 0, 1, 1]: 1.000053838844293 Prediction for [1, 0, 0, 0, 1, 1, 0, 0]: 0.0 Prediction for [1, 0, 0, 0, 1, 1, 0, 1]: 0.0 Prediction for [1, 0, 0, 0, 1, 1, 1, 0]: 0.0 Prediction for [1, 0, 0, 0, 1, 1, 1, 1]: 0.0 Prediction for [1, 0, 0, 1, 0, 0, 0, 0]: 0.0 Prediction for [1, 0, 0, 1, 0, 0, 0, 1]: 5.5847984548051954E-5 Prediction for [1, 0, 0, 1, 0, 0, 1, 0]: 0.0 Prediction for [1, 0, 0, 1, 0, 0, 1, 1]: 0.0 Prediction for [1, 0, 0, 1, 0, 1, 0, 0]: 0.0 Prediction for [1, 0, 0, 1, 0, 1, 0, 1]: 0.9998508359008422 Prediction for [1, 0, 0, 1, 0, 1, 1, 0]: 0.0 Prediction for [1, 0, 0, 1, 0, 1, 1, 1]: 0.999589947501633 Prediction for [1, 0, 0, 1, 1, 0, 0, 0]: 0.0 Prediction for [1, 0, 0, 1, 1, 0, 0, 1]: 0.0 Prediction for [1, 0, 0, 1, 1, 0, 1, 0]: 0.0 Prediction for [1, 0, 0, 1, 1, 0, 1, 1]: 2.807210240041158E-4 Prediction for [1, 0, 0, 1, 1, 1, 0, 0]: 0.0 Prediction for [1, 0, 0, 1, 1, 1, 0, 1]: 1.0001931269944295 Prediction for [1, 0, 0, 1, 1, 1, 1, 0]: 0.0 Prediction for [1, 0, 0, 1, 1, 1, 1, 1]: 0.0 Prediction for [1, 0, 1, 0, 0, 0, 0, 0]: 0.0 Prediction for [1, 0, 1, 0, 0, 0, 0, 1]: 2.3369076458656934E-4 Prediction for [1, 0, 1, 0, 0, 0, 1, 0]: 0.0 Prediction for [1, 0, 1, 0, 0, 0, 1, 1]: 1.0000530463166948 Prediction for [1, 0, 1, 0, 0, 1, 0, 0]: 0.0 Prediction for [1, 0, 1, 0, 0, 1, 0, 1]: 0.0 Prediction for [1, 0, 1, 0, 0, 1, 1, 0]: 0.0 Prediction for [1, 0, 1, 0, 0, 1, 1, 1]: 0.9984847704618565 Prediction for [1, 0, 1, 0, 1, 0, 0, 0]: 0.0 Prediction for [1, 0, 1, 0, 1, 0, 0, 1]: 0.0 Prediction for [1, 0, 1, 0, 1, 0, 1, 0]: 0.0 Prediction for [1, 0, 1, 0, 1, 0, 1, 1]: 0.0012304104588602982 Prediction for [1, 0, 1, 0, 1, 1, 0, 0]: 0.0 Prediction for [1, 0, 1, 0, 1, 1, 0, 1]: 0.9988902305503888 Prediction for [1, 0, 1, 0, 1, 1, 1, 0]: 0.0 Prediction for [1, 0, 1, 0, 1, 1, 1, 1]: 0.0013929410989526048 Prediction for [1, 0, 1, 1, 0, 0, 0, 0]: 0.0 Prediction for [1, 0, 1, 1, 0, 0, 0, 1]: 0.0 Prediction for [1, 0, 1, 1, 0, 0, 1, 0]: 0.0 Prediction for [1, 0, 1, 1, 0, 0, 1, 1]: 1.0002552991372369 Prediction for [1, 0, 1, 1, 0, 1, 0, 0]: 0.0 Prediction for [1, 0, 1, 1, 0, 1, 0, 1]: 1.0002735125659727 Prediction for [1, 0, 1, 1, 0, 1, 1, 0]: 0.0 Prediction for [1, 0, 1, 1, 0, 1, 1, 1]: 0.0 Prediction for [1, 0, 1, 1, 1, 0, 0, 0]: 0.0 Prediction for [1, 0, 1, 1, 1, 0, 0, 1]: 0.0 Prediction for [1, 0, 1, 1, 1, 0, 1, 0]: 0.0 Prediction for [1, 0, 1, 1, 1, 0, 1, 1]: 0.0 Prediction for [1, 0, 1, 1, 1, 1, 0, 0]: 0.0 Prediction for [1, 0, 1, 1, 1, 1, 0, 1]: 0.0016007416738244018 Prediction for [1, 0, 1, 1, 1, 1, 1, 0]: 0.0 Prediction for [1, 0, 1, 1, 1, 1, 1, 1]: 0.9992947996206096 Prediction for [1, 1, 0, 0, 0, 0, 0, 0]: 0.0 Prediction for [1, 1, 0, 0, 0, 0, 0, 1]: 1.0001053458187812 Prediction for [1, 1, 0, 0, 0, 0, 1, 0]: 0.0 Prediction for [1, 1, 0, 0, 0, 0, 1, 1]: 0.0 Prediction for [1, 1, 0, 0, 0, 1, 0, 0]: 0.0 Prediction for [1, 1, 0, 0, 0, 1, 0, 1]: 0.9995775815180679 Prediction for [1, 1, 0, 0, 0, 1, 1, 0]: 0.0 Prediction for [1, 1, 0, 0, 0, 1, 1, 1]: 1.0008752175214708 Prediction for [1, 1, 0, 0, 1, 0, 0, 0]: 0.0 Prediction for [1, 1, 0, 0, 1, 0, 0, 1]: 0.0 Prediction for [1, 1, 0, 0, 1, 0, 1, 0]: 0.0 Prediction for [1, 1, 0, 0, 1, 0, 1, 1]: 0.0 Prediction for [1, 1, 0, 0, 1, 1, 0, 0]: 0.0 Prediction for [1, 1, 0, 0, 1, 1, 0, 1]: 7.62632073844749E-4 Prediction for [1, 1, 0, 0, 1, 1, 1, 0]: 0.0 Prediction for [1, 1, 0, 0, 1, 1, 1, 1]: 6.25783094595711E-4 Prediction for [1, 1, 0, 1, 0, 0, 0, 0]: 0.0 Prediction for [1, 1, 0, 1, 0, 0, 0, 1]: 0.0 Prediction for [1, 1, 0, 1, 0, 0, 1, 0]: 0.0 Prediction for [1, 1, 0, 1, 0, 0, 1, 1]: 1.0001554066923442 Prediction for [1, 1, 0, 1, 0, 1, 0, 0]: 0.0 Prediction for [1, 1, 0, 1, 0, 1, 0, 1]: 0.0 Prediction for [1, 1, 0, 1, 0, 1, 1, 0]: 0.0 Prediction for [1, 1, 0, 1, 0, 1, 1, 1]: 3.4988672418911904E-4 Prediction for [1, 1, 0, 1, 1, 0, 0, 0]: 0.0 Prediction for [1, 1, 0, 1, 1, 0, 0, 1]: 0.0 Prediction for [1, 1, 0, 1, 1, 0, 1, 0]: 0.0 Prediction for [1, 1, 0, 1, 1, 0, 1, 1]: 0.0 Prediction for [1, 1, 0, 1, 1, 1, 0, 0]: 0.0 Prediction for [1, 1, 0, 1, 1, 1, 0, 1]: 7.196000341442854E-4 Prediction for [1, 1, 0, 1, 1, 1, 1, 0]: 0.0 Prediction for [1, 1, 0, 1, 1, 1, 1, 1]: 0.9997377076301417 Prediction for [1, 1, 1, 0, 0, 0, 0, 0]: 0.0 Prediction for [1, 1, 1, 0, 0, 0, 0, 1]: 0.005120553154234209 Prediction for [1, 1, 1, 0, 0, 0, 1, 0]: 0.0 Prediction for [1, 1, 1, 0, 0, 0, 1, 1]: 0.9993977119139466 Prediction for [1, 1, 1, 0, 0, 1, 0, 0]: 0.0 Prediction for [1, 1, 1, 0, 0, 1, 0, 1]: 0.9967633518764378 Prediction for [1, 1, 1, 0, 0, 1, 1, 0]: 0.0 Prediction for [1, 1, 1, 0, 0, 1, 1, 1]: 0.009537857931912974 Prediction for [1, 1, 1, 0, 1, 0, 0, 0]: 0.0 Prediction for [1, 1, 1, 0, 1, 0, 0, 1]: 0.996080472054107 Prediction for [1, 1, 1, 0, 1, 0, 1, 0]: 0.0 Prediction for [1, 1, 1, 0, 1, 0, 1, 1]: 8.731463822684304E-4 Prediction for [1, 1, 1, 0, 1, 1, 0, 0]: 0.0 Prediction for [1, 1, 1, 0, 1, 1, 0, 1]: 0.005090637076019533 Prediction for [1, 1, 1, 0, 1, 1, 1, 0]: 0.0 Prediction for [1, 1, 1, 0, 1, 1, 1, 1]: 0.9924698020086469 Prediction for [1, 1, 1, 1, 0, 0, 0, 0]: 0.0 Prediction for [1, 1, 1, 1, 0, 0, 0, 1]: 0.9992275293460162 Prediction for [1, 1, 1, 1, 0, 0, 1, 0]: 0.0 Prediction for [1, 1, 1, 1, 0, 0, 1, 1]: 0.0 Prediction for [1, 1, 1, 1, 0, 1, 0, 0]: 0.0 Prediction for [1, 1, 1, 1, 0, 1, 0, 1]: 0.0 Prediction for [1, 1, 1, 1, 0, 1, 1, 0]: 0.0 Prediction for [1, 1, 1, 1, 0, 1, 1, 1]: 7.154212054905074E-4 Prediction for [1, 1, 1, 1, 1, 0, 0, 0]: 0.0 Prediction for [1, 1, 1, 1, 1, 0, 0, 1]: 0.0 Prediction for [1, 1, 1, 1, 1, 0, 1, 0]: 0.0 Prediction for [1, 1, 1, 1, 1, 0, 1, 1]: 0.9991975677567666 Prediction for [1, 1, 1, 1, 1, 1, 0, 0]: 0.0 Prediction for [1, 1, 1, 1, 1, 1, 0, 1]: 0.0 Prediction for [1, 1, 1, 1, 1, 1, 1, 0]: 0.0 Prediction for [1, 1, 1, 1, 1, 1, 1, 1]: 3.634046610150321E-4 BUILD SUCCESSFUL (total time: 40 seconds)

Yeah but it still works tho if you scan the QR Code

Autoruns is one of the rare tools to get a complete list of all important entries in terms of autostart programs, services, drivers, tasks, handlers, codecs and so on, sorted by categories. To be honest, I never felt the need to remove such entries shown in your screenshot. Any regular entries will stay in my system as they are. For me, Autoruns is a perfect tool in finding remnants of already uninstalled programs or services. I use it regularly for this purpose and for additional control.

If by manually, you imply only by editing the Preferences file, then not true, you add to the list whenever you download to a new location, and you can clear this list from within the download dialog -

There is very good news! @Miles Prower found results.asp in a Win ME preinstalled file! Currently the page is still static, so the wrong updates are displayed. Unfortunately we are still missing the results.asp for the selection of updates i.e. for "Important Updates and Service Packs" and for "Windows x". Here is a short video:

any UXP

Hi @Ryder252, hello from Belgium and welcome to MSFN! I wish you to enjoy the forums! Have a nice day. hpwamr