Package tv.floe.metronome.eval

Examples of tv.floe.metronome.eval.Evaluation


 
 
  public static void evaluateModel( Matrix inputs, Matrix labels, BaseMultiLayerNeuralNetworkVectorized model ) throws IOException {
   

    Evaluation eval = new Evaluation();
    //BaseMultiLayerNeuralNetworkVectorized load = BaseMultiLayerNeuralNetworkVectorized.loadFromFile(new FileInputStream(new File(modelLocation)));
   
//    while (iterator.hasNext()) {
     
//      DataSet inputs = iterator.next();

//      Matrix in = inputs.getFirst();
//      Matrix outcomes = inputs.getSecond();

    Matrix predicted = model.predict(inputs);
   
    eval.eval( labels, predicted );
     
//    }
   
   
   
    log.warn( "evaluateModel" );
    log.info( eval.stats() );   
   
    //writeReportToDisk( eval, pathForReport );
   
  }   
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  }   
 
  public static void evaluateSavedModel( BaseDatasetIterator iterator, String modelLocation, String pathForReport ) throws IOException {
   

    Evaluation eval = new Evaluation();
    BaseMultiLayerNeuralNetworkVectorized load = BaseMultiLayerNeuralNetworkVectorized.loadFromFile(new FileInputStream(new File(modelLocation)));
   
    while (iterator.hasNext()) {
     
      DataSet inputs = iterator.next();

      Matrix in = inputs.getFirst();
      Matrix outcomes = inputs.getSecond();
      Matrix predicted = load.predict(in);
      eval.eval( outcomes, predicted );
     
    }
   
   
   
   
    log.info( eval.stats() );   
   
    writeReportToDisk( eval, pathForReport );
   
  }
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