Package tv.floe.metronome.deeplearning.datasets

Examples of tv.floe.metronome.deeplearning.datasets.DataSet

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    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(in);
      eval.eval( outcomes, predicted );
     
    }
   
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    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 );
     
    }
   
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    MnistHDFSDataSetIterator hdfs_fetcher = new MnistHDFSDataSetIterator( batchSize, 1, txt_reader );
    DataSet hdfs_recordBatch = hdfs_fetcher.next();
   
    Matrix hdfs_input = hdfs_recordBatch.getFirst();
    Matrix hdfs_labels = hdfs_recordBatch.getSecond();     
   
    //ModelTester.evaluateModel( recordBatch.getFirst(), recordBatch.getSecond(), dbn);
     
   
    int[] hiddenLayerSizes = new int[] {2,2,2};
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Related Classes of tv.floe.metronome.deeplearning.datasets.DataSet

  • org.apache.commons.math3.random.MersenneTwister
  • org.apache.mahout.math.DenseMatrix
  • org.apache.mahout.math.Matrix
  • tv.floe.metronome.deeplearning.datasets.fetchers.BaseDataFetcher
  • tv.floe.metronome.deeplearning.dbn.iterativereduce.Test_DBN_IR_MNIST
  • tv.floe.metronome.deeplearning.dbn.iterativereduce.WorkerNode
  • tv.floe.metronome.deeplearning.dbn.model.evaluation.ModelTester
  • tv.floe.metronome.deeplearning.neuralnetwork.dbn.dataset.mnist.Test_DBN_Mnist_Dataset
  • tv.floe.metronome.deeplearning.neuralnetwork.io.TestSaveLoadModel
  • tv.floe.metronome.deeplearning.rbm.datasets.mnist.TestMNIST_On_RBMs
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