Package quickml.supervised.classifier.decisionTree.scorers

Examples of quickml.supervised.classifier.decisionTree.scorers.SplitDiffScorer

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        Assert.assertTrue(String.format("Error should be < 0.1 but was %s (prob=%s, desired=0.05)", error, correctedMinorityInstanceOccurance), error < 0.01);
    }

    @Test
    public void simpleBmiTest() throws IOException, ClassNotFoundException {
        final TreeBuilder tb = new TreeBuilder(new SplitDiffScorer());
        final RandomForestBuilder urfb = new RandomForestBuilder(tb);
        final DownsamplingClassifierBuilder dpmb = new DownsamplingClassifierBuilder(urfb, 0.1);

        final List<Instance<AttributesMap>> instances = TreeBuilderTestUtils.getIntegerInstances(1000);
        final PredictiveModelWithDataBuilder<AttributesMap ,DownsamplingClassifier> wb = new PredictiveModelWithDataBuilder<>(dpmb);
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    public void simpleBmiTest() throws Exception {
        Set<String> whiteList = new HashSet<>();
        whiteList.add("weight");
        whiteList.add("height");
        final List<Instance<AttributesMap>> instances = TreeBuilderTestUtils.getInstances(10000);
        final TreeBuilder tb = new TreeBuilder(new SplitDiffScorer()).splitPredictiveModel("gender", whiteList);
        final RandomForestBuilder rfb = new RandomForestBuilder(tb);
        final SplitOnAttributeClassifierBuilder cpmb = new SplitOnAttributeClassifierBuilder("gender", rfb, 10, 0.1, whiteList, 1);
        final long startTime = System.currentTimeMillis();
        final SplitOnAttributeClassifier splitOnAttributeClassifier = cpmb.buildPredictiveModel(instances);
        final RandomForest randomForest = (RandomForest) splitOnAttributeClassifier.getDefaultPM();
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    private PredictiveModelWithDataBuilder<AttributesMap ,SplitOnAttributeClassifier> getWrappedUpdatablePredictiveModelBuilder() {
        Set<String> whiteList = new HashSet<>();
        whiteList.add("weight");
        whiteList.add("height");
        final TreeBuilder tb = new TreeBuilder(new SplitDiffScorer()).splitPredictiveModel("gender", whiteList);
        final RandomForestBuilder urfb = new RandomForestBuilder(tb);
        final SplitOnAttributeClassifierBuilder ucpmb = new SplitOnAttributeClassifierBuilder("gender", urfb, 10, 0.1, whiteList, 1);
        return new PredictiveModelWithDataBuilder<>(ucpmb);
    }
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Related Classes of quickml.supervised.classifier.decisionTree.scorers.SplitDiffScorer

  • quickml.Benchmarks
  • quickml.supervised.classifier.decisionTree.TreeBuilderFactory
  • quickml.supervised.classifier.decisionTree.TreeBuilderTest
  • quickml.supervised.classifier.downsampling.DownsamplingClassifierBuilderTest
  • quickml.supervised.classifier.randomForest.RandomForestBuilderTest
  • quickml.supervised.classifier.splitOnAttribute.SplitOnAttributeClassifierBuilderTest
  • quickml.supervised.classifier.temporallyWeightClassifier.TemporallyReweightedClassifierBuilderTest
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