Examples of train()

Examples of resys.impl.svdplusplus.SVDPlusPlusRecommender.train()

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        System.out.println("data model is load into memory....");

        Recommender recommender = new SVDPlusPlusRecommender(datamodel);
        // Recommender recommender = new SVDRecommender(datamodel);

        recommender.train();

    }

}
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Examples of seekfeel.miners.supervised.SupervisedPanel.train()

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        // System.out.println(validator.validate());
      
        ArrayList<SupportedFeature> supportedFeatures = new ArrayList<SupportedFeature>();
        supportedFeatures.add(SupportedFeature.TaggedStems);
        SupervisedPanel sp = new SupervisedPanel(PropertiesGetter.getProperty("AnnotatedTweets"),supportedFeatures,new TweeterCorpusLoader());
        sp.train();

    }
}
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Examples of tv.floe.metronome.classification.neuralnetworks.networks.MultiLayerPerceptronNetwork.train()

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    for ( int x = 0; x < 40000; x++ ) {
     
     
         

      mlp_network.train(v0_out, v0);
      mlp_network.train(v1_out, v1);
      mlp_network.train(v2_out, v2);
      mlp_network.train(v3_out, v3);

     
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Examples of tv.floe.metronome.deeplearning.neuralnetwork.core.LogisticRegression.train()

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    for (int i = 0; i < 10000; i++) {
     
      //logRegression.trainWithAdagrad(x, y);
      logRegression.train(x_xor_Matrix, y_xor_Matrix, 0.001);

    }
   
    Matrix predictions = logRegression.predict(x_xor_Matrix);
   
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Examples of zdenekdrahos.AI.KohonenMap.IKohonenMap.train()

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    @Test
    public void testTrain() throws FileNotFoundException {
        IKohonenMap map = new KohonenMap();
        map.setData(getExampleInput());
        map.train(alfa, groupsCount, iterationsCount);
        Double[][] weights = map.getWeights();
        for (int i = 0; i < weights.length; i++) {
            for (int j = 0; j < weights[0].length; j++) {
                assertTrue(weights[i][j] - expectedWeights[i][j] < 0.1);
            }
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Examples of zdenekdrahos.AI.KohonenMap.KohonenMap.train()

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    @Test
    public void testTrain() throws FileNotFoundException {
        IKohonenMap map = new KohonenMap();
        map.setData(getExampleInput());
        map.train(alfa, groupsCount, iterationsCount);
        Double[][] weights = map.getWeights();
        for (int i = 0; i < weights.length; i++) {
            for (int j = 0; j < weights[0].length; j++) {
                assertTrue(weights[i][j] - expectedWeights[i][j] < 0.1);
            }
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Examples of zdenekdrahos.AI.Training.ITraining.train()

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        in.targets = output;

        ITrainingBuilder trainBuilder = new TrainingBuilder();
        ITraining train = trainBuilder.build();
        TrainingOutput out = new TrainingOutput(0.00005);
        train.train(network, in, out);
        System.out.printf("Solution in %d iteration, minError = %f, lastError: %f\n\n", out.lastIterationNumber, out.minError, out.lastError);

        final XYSeries series2 = new XYSeries("Prediction");

        SimulationIterator iterator;
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