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index.html
10
index.html
@ -699,15 +699,17 @@ NN.Network.Stochastic = function(inNetwork, inTrainingSet, inIterations)
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[ 0.99, 0.85],
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[ 0.99, 0.85],
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[ 1.2, 1.05]
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[ 1.2, 1.05]
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];
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];
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let goals = [
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[1, 1, 0],
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[0, 0, 1]
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];
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var layer1 = NN.Layer.Create(1, 1);
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var layer1 = NN.Layer.Create(1, 1);
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layer1.Forward.Matrix = matrix1;
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layer1.Forward.Matrix = matrix1;
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var layer2 = NN.Layer.Create(1, 1);
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layer2.Forward.Matrix = matrix2;
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let stage1 = NN.Layer.Forward(layer1, typeA);
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let stage1 = NN.Layer.Forward(layer1, typeA);
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let stage1Error = NN.Layer.Error(layer1, goals);
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console.log(stage1);
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console.log(stage1Error);
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</script>
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</script>
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30
nn.test.js
30
nn.test.js
@ -19,17 +19,14 @@ let typeB = [
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Deno.test("check.forward", ()=>
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Deno.test("check.forward", ()=>
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{
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{
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let training = [];
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let matrix1 = [
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let stages = [];
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[-0.43662948305036675, -0.368590640707799, -0.23227179558890843],
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let layers = [
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[-0.004292653969505622, 0.38670055222186317, -0.2478421495365568],
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[
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[0.738181366836224, 0.3389203747353555, 0.4920200816404332]
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[-0.43662948305036675, -0.368590640707799, -0.23227179558890843],
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];
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[-0.004292653969505622, 0.38670055222186317, -0.2478421495365568],
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[0.738181366836224, 0.3389203747353555, 0.4920200816404332]
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let matrix2 = [
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],
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[0.5793881115472015, 0.9732593374796092, 0.15207639877016987, -0.5356575655337803]
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[
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[0.5793881115472015, 0.9732593374796092, 0.15207639877016987, -0.5356575655337803]
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]
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];
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];
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let typeA = [
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let typeA = [
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@ -40,11 +37,14 @@ Deno.test("check.forward", ()=>
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[ 0.99, 0.85],
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[ 0.99, 0.85],
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[ 1.2, 1.05]
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[ 1.2, 1.05]
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];
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];
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let goals = [
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[1, 1, 0],
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[0, 0, 1]
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];
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Label(training, typeA, [1]);
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let layers = [matrix1];
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stages.push(training[0]);
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let stages = Forward(Methods.Mutate.Pad(typeA), layers);
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Forward(stages, layers);
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Backward(stages, layers, goals, 0.1);
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console.log(stages);
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});
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});
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/*
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/*
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15
nn.ts
15
nn.ts
@ -16,22 +16,25 @@ const Label = (inSet:any, inData:Cloud.M, inLabel:Cloud.V):N =>
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return inSet;
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return inSet;
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};
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};
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const Forward = (inStages:N, inLayers:N):Cloud.M =>
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const Forward = (inData:Cloud.M, inLayers:N):N =>
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{
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{
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let i:number;
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let i:number;
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let process = (index:number):Cloud.M => M.Batch.Sigmoid(M.Batch.Affine(inStages[index], inLayers[index]));
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let stages = [inData];
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let process = (index:number):Cloud.M => M.Batch.Sigmoid(M.Batch.Affine(stages[index], inLayers[index]));
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for(i=0; i<inLayers.length-1; i++)
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for(i=0; i<inLayers.length-1; i++)
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{
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{
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inStages[i+1] = M.Mutate.Pad(process(i));
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stages[i+1] = M.Mutate.Pad(process(i));
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}
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}
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inStages[i+1] = process(i);
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stages[i+1] = process(i);
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return inStages[i+1];
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return stages;
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};
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};
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const Backward = (inStages:N, inLayers:N, inGoals:Cloud.M, inRate:number):N =>
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const Backward = (inStages:N, inLayers:N, inGoals:Cloud.M, inRate:number):N =>
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{
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{
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let i:number;
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let i:number;
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let errorBack:Cloud.M = M.Batch.Subtract(Forward(inStages, inLayers), inGoals);
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let errorBack:Cloud.M = M.Batch.Subtract(inStages[inStages.length-1], inGoals);
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console.log(errorBack);
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for(i=inLayers.length-1; i>=0; i--)
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for(i=inLayers.length-1; i>=0; i--)
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{
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{
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