Examples of extractLabels()

Examples of org.apache.mahout.classifier.df.data.Data.extractLabels()

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    DecisionForest forestOne = forestBuilder.build(nbtrees);
    sumTimeOne += System.currentTimeMillis() - time;
    numNodesOne += forestOne.nbNodes();
   
    // compute the test set error (Selection Error), and mean tree error (One Tree Error),
    double[] testLabels = test.extractLabels();
    double[][] predictions = new double[test.size()][];
   
    forestM.classify(test, predictions);
    double[] sumPredictions = new double[test.size()];
    Arrays.fill(sumPredictions, 0.0);
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Examples of org.apache.mahout.classifier.df.data.Data.extractLabels()

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    DecisionForest forestOne = forestBuilder.build(nbtrees);
    sumTimeOne += System.currentTimeMillis() - time;
    numNodesOne += forestOne.nbNodes();
   
    // compute the test set error (Selection Error), and mean tree error (One Tree Error),
    double[] testLabels = test.extractLabels();
    double[] predictions = new double[test.size()];
   
    forestM.classify(test, predictions);
    sumTestErrM += ErrorEstimate.errorRate(testLabels, predictions);
   
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Examples of org.apache.mahout.df.data.Data.extractLabels()

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    log.info("Splitting the data");
    Data train = data.clone();
    Data test = train.rsplit(rng, (int) (data.size() * 0.1));
   
    int[] trainLabels = train.extractLabels();
    int[] testLabels = test.extractLabels();
   
    DefaultTreeBuilder treeBuilder = new DefaultTreeBuilder();
   
    SequentialBuilder forestBuilder = new SequentialBuilder(rng, treeBuilder, train);
   
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Examples of org.apache.mahout.df.data.Data.extractLabels()

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    Data train = data.clone();
    Data test = train.rsplit(rng, (int) (data.size() * 0.1));
   
    int[] trainLabels = train.extractLabels();
    int[] testLabels = test.extractLabels();
   
    DefaultTreeBuilder treeBuilder = new DefaultTreeBuilder();
   
    SequentialBuilder forestBuilder = new SequentialBuilder(rng, treeBuilder, train);

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