Package org.encog.ml.data.buffer

Examples of org.encog.ml.data.buffer.BufferedNeuralDataSet.beginLoad()

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      final boolean headers) {
    binFile.delete();
    final CSVNeuralDataSet csv = new CSVNeuralDataSet(csvFile.toString(),
        inputCount, outputCount, false);
    final BufferedNeuralDataSet buffer = new BufferedNeuralDataSet(binFile);
    buffer.beginLoad(inputCount, outputCount);
    for (final MLDataPair pair : csv) {
      buffer.add(pair);
    }
    buffer.endLoad();
  }
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        (new File(binFile)).delete();
        CSVNeuralDataSet csv = new CSVNeuralDataSet(csvFile.toString(),
               inputCount, outputCount, headers);
        BufferedNeuralDataSet buffer = new BufferedNeuralDataSet(new File(binFile));
        buffer.beginLoad(inputCount, outputCount);
        for(MLDataPair pair : csv)
        {
            buffer.add(pair);
        }
        buffer.endLoad();
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       binFile.delete();
       ReadCSV csv = new ReadCSV(csvFile.toString(), headers, format);
      
       BufferedNeuralDataSet buffer = new BufferedNeuralDataSet(binFile);
       buffer.beginLoad(input.length, ideal.length);
       while(csv.next())
       {
         BasicMLData inputData = new BasicMLData(input.length);
         BasicMLData idealData = new BasicMLData(ideal.length);
        
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  public void testBufferData() throws Exception
  {
    new File(FILENAME).delete();
    BufferedNeuralDataSet set = new BufferedNeuralDataSet(new File(FILENAME));
    set.beginLoad(2, 1);
    for(int i=0;i<XOR.XOR_INPUT.length;i++) {
      BasicMLData input = new BasicMLData(XOR.XOR_INPUT[i]);
      BasicMLData ideal = new BasicMLData(XOR.XOR_IDEAL[i]);
      set.add(input,ideal);
    }
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      BufferedNeuralDataSet trainingData = new BufferedNeuralDataSet(file);

      MLDataPair pair = BasicMLDataPair.createPair(input,
          output);
      trainingData.beginLoad(input, output);
      for (int i = 0; i < elements; i++) {
        trainingData.add(pair);
      }
      trainingData.endLoad();
    }
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