runbp.m

patten regnization source从1-14章能运行

ErrorsLastNEpochs = zeros(1,NEpochs);
TestErrorsLastNEpochs = zeros(1,NEpochs);
startEpoch = totalNEpochs + 1;

for epoch = 1:NEpochs,
  sumSqrError = 0.0;
  sumSqrTestError = 0.0;
  outputWGrad = zeros(size(outputWeights));
  hiddenWGrad = zeros(size(hiddenWeights));
  for pat = 1:nTrainingPats,
    % 傈规氢 菩胶(pass)
    inp = [input(:,pat)',[1]]';
    hiddenNetInputs = hiddenWeights * inp;
    hiddenStates = sigmoidFunc(hiddenNetInputs);
    hidStatesBias = [[hiddenStates]',[1]]';
    outputNetInputs = outputWeights * hidStatesBias;
    outputStates = sigmoidFunc(outputNetInputs);

    % 开规氢 菩胶(pass)
    targetStates = target(:,pat);
    error = outputStates - targetStates;
    sumSqrError = sumSqrError + dot(error,error);
    outputDel = outputDeltas(outputStates, targetStates);
    outputWGrad = outputWGrad + outputDel * hidStatesBias';
    hiddenDel = hiddenDeltas(outputDel,hidStatesBias,outputWeights);
    hiddenWGrad = hiddenWGrad + hiddenDel(1:nHidden,:) * inp';
  end
  % epoch狼 付瘤阜俊 啊吝摹 盎脚 
  outputWChange = eta * outputWGrad;
  outputWeights = outputWeights + outputWChange;
  hiddenWChange = eta * hiddenWGrad;
  hiddenWeights = hiddenWeights + hiddenWChange;

  %抛胶飘 菩畔栏肺 匙飘况农狼 己瓷 矫氰
  for pat = (nTrainingPats+1):nPats
    % 傈氢氢 菩胶(pass)
    inp = [input(:,pat)',[1]]';
    hiddenNetInputs = hiddenWeights * inp;
    hiddenStates = sigmoidFunc(hiddenNetInputs);
    hidStatesBias = [[hiddenStates]',[1]]';
    outputNetInputs = outputWeights * hidStatesBias;
    outputStates = sigmoidFunc(outputNetInputs);
    targetStates = target(:,pat);
    error = outputStates - targetStates;
    sumSqrTestError = sumSqrTestError + dot(error,error);
  end

  %% epoch狼 付瘤阜俊 夸距 烹拌 免仿
  gradSize = norm([hiddenWGrad(:);outputWGrad(:)]);
  totalNEpochs = totalNEpochs + 1;
  MSE = sumSqrError/nTrainingPats;
  TestMSE = sumSqrTestError/nTestPats;
  if totalNEpochs == 1
      startError = MSE;
  end
  ErrorsLastNEpochs(1,epoch) = MSE;
  TestErrorsLastNEpochs(1,epoch) = TestMSE;
  fprintf(1,'%d  MSError=%f, MSTestError=%f, |G|=%f\n',...
            totalNEpochs,MSE,TestMSE,gradSize);
end

clf; 
if totalNEpochs > minEpochsPerErrorPlot
  epochs = [1:totalNEpochs];
end

% 切嚼 菩畔 笼钦俊 措茄 切嚼 目宏 敲吩
errorsPerEpoch(1,startEpoch:totalNEpochs) = ErrorsLastNEpochs;
subplot(2,1,1), ...
  axis([1 max(minEpochsPerErrorPlot,totalNEpochs) 0 startError]),  hold on, ...
  plot(epochs(1,1:totalNEpochs),errorsPerEpoch(1,1:totalNEpochs)),...
  title('Mean Squared Error on the Training Set'), ...
  xlabel('Learning Epoch'), ...
  ylabel('MSE');

% 抛胶飘 菩畔 笼钦俊 措茄 切嚼 目宏 敲吩
TestErrorsPerEpoch(1,startEpoch:totalNEpochs) = TestErrorsLastNEpochs;
subplot(2,1,2), ...
  axis([1 max(minEpochsPerErrorPlot,totalNEpochs) 0 startError]),  hold on, ...
  plot(epochs(1,1:totalNEpochs),TestErrorsPerEpoch(1,1:totalNEpochs)), ...
  title('Mean Squared Error on the Test Set'), ...
  xlabel('Learning Epoch'), ...
  ylabel('MSE');