saving and retrieving trained NN

[gitnichi]

Hello, thank you for writing such a good code, it's really easy to get it running and experimenting quickly! I'm using the NNs to classify a data set unrelated to weka, therefore I need to train my NN before using it and then use the trained NN with data from the users, in a live fashion. Since training takes several hours, I can't afford to train it every time I need to use it. I haven't found any methods in your code to save the NN's weights, nor configuration. I found in a weka related page the following code:

Debug.saveToFile(filename+"_nn.dat", nn); then, to load in the classifying part:
SerializedClassifier classifier = new SerializedClassifier(); classifier.setModelFile(new File("/path/to/weka-neural-network"));

Will this work with your code,i.e. if I use instead of "SerializedClassifier" NNParams params = new NNParams(); params.numClasses = 10; // 10 digits to classify params.hiddenLayerParams = myNNconfig and then classifier.setModelFile(new File("/path/to/weka-neural-network"));?

Thank you very much for your help!

[gitnichi]

I've already solved it, using the write/readCSV of the MatrixUtils class, here is the code if someone needs it, just put into the NeuralNetwork class the following methods: /**

• Loads NN from file, with parameters supplied in myParms
• note: doesn't check matrices match sizes!

• it's up to the developer to specify them properly when invoking the NN constructor */

  public void loadNN(String filename){

  mySoftmax = myParams.numClasses > 1;
  myNumOutputs = myParams.numClasses;
  
  // Add null params for layer 0, which is just the input and last layer, which is just output.
  myLayerParams = new NNParams.NNLayerParams[myParams.hiddenLayerParams.length+2];
  System.arraycopy(myParams.hiddenLayerParams, 0, myLayerParams, 1, myParams.hiddenLayerParams.length);
  myLayerParams[myLayerParams.length-1] = new NNParams.NNLayerParams(myNumOutputs);
  myParams.numThreads = myParams.numThreads > 0 ? myParams.numThreads : Runtime.getRuntime().availableProcessors();
  myExecutorService = Executors.newFixedThreadPool(myParams.numThreads);
  
  int numLayers = myLayerParams.length;
  
  initThetas();
  
  for (int layer = 1; layer < numLayers; layer++)
      try{
      myThetas[layer]=MatrixUtils.readCSV(filename+"_l"+layer+".csv",',', 0);            
      }catch(Exception e) {System.out.println(e.toString());}

  }