Package org.apache.mahout.df.ref

Examples of org.apache.mahout.df.ref.SequentialBuilder.build()

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                                                                              // log2(M)+1
    treeBuilder.setM(m);
   
    long time = System.currentTimeMillis();
    log.info("Growing a forest with m={}", m);
    DecisionForest forestM = forestBuilder.build(nbtrees, errorM);
    sumTimeM += System.currentTimeMillis() - time;
    numNodesM += forestM.nbNodes();
   
    double oobM = ErrorEstimate.errorRate(trainLabels, errorM.computePredictions(rng)); // oob error estimate
                                                                                        // when m = log2(M)+1
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    ForestPredictions errorOne = new ForestPredictions(train.size(), nblabels); // oob error when using m = 1
    treeBuilder.setM(1);
   
    time = System.currentTimeMillis();
    log.info("Growing a forest with m=1");
    DecisionForest forestOne = forestBuilder.build(nbtrees, errorOne);
    sumTimeOne += System.currentTimeMillis() - time;
    numNodesOne += forestOne.nbNodes();
   
    double oobOne = ErrorEstimate.errorRate(trainLabels, errorOne.computePredictions(rng)); // oob error
                                                                                            // estimate when m
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    ForestPredictions errorM = new ForestPredictions(dataSize, nblabels); // oob error when using m = log2(M)+1
    treeBuilder.setM(m);

    long time = System.currentTimeMillis();
    log.info("Growing a forest with m=" + m);
    DecisionForest forestM = forestBuilder.build(nbtrees, errorM);
    sumTimeM += System.currentTimeMillis() - time;

    double oobM = ErrorEstimate.errorRate(trainLabels, errorM.computePredictions(rng)); // oob error estimate when m = log2(M)+1

    // grow a forest with m=1
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    ForestPredictions errorOne = new ForestPredictions(dataSize, nblabels); // oob error when using m = 1
    treeBuilder.setM(1);

    time = System.currentTimeMillis();
    log.info("Growing a forest with m=1");
    DecisionForest forestOne = forestBuilder.build(nbtrees, errorOne);
    sumTimeOne += System.currentTimeMillis() - time;

    double oobOne = ErrorEstimate.errorRate(trainLabels, errorOne.computePredictions(rng)); // oob error estimate when m = 1

    // compute the test set error (Selection Error), and mean tree error (One Tree Error),
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