Examples with ElasticNetLogisticTrainer edu.neu.ccs.pyramid.classification.logistic_regression.ElasticNetLogisticTrainer used on opensource projects

Example 1 with ElasticNetLogisticTrainer

use of edu.neu.ccs.pyramid.classification.logistic_regression.ElasticNetLogisticTrainer in project pyramid by cheng-li.

the class ENCBMOptimizer method updateBinaryClassifier.

@Override
protected void updateBinaryClassifier(int component, int label, MultiLabelClfDataSet activeDataset, double[] activeGammas) {
    StopWatch stopWatch = new StopWatch();
    stopWatch.start();
    if (cbm.binaryClassifiers[component][label] == null || cbm.binaryClassifiers[component][label] instanceof PriorProbClassifier) {
        cbm.binaryClassifiers[component][label] = new LogisticRegression(2, activeDataset.getNumFeatures());
    }
    int[] binaryLabels = DataSetUtil.toBinaryLabels(activeDataset.getMultiLabels(), label);
    double[][] targetsDistribution = DataSetUtil.labelsToDistributions(binaryLabels, 2);
    ElasticNetLogisticTrainer elasticNetLogisticTrainer = new ElasticNetLogisticTrainer.Builder((LogisticRegression) cbm.binaryClassifiers[component][label], activeDataset, 2, targetsDistribution, activeGammas).setRegularization(regularizationBinary).setL1Ratio(l1RatioBinary).setLineSearch(lineSearch).build();
    elasticNetLogisticTrainer.setActiveSet(activeSet);
    elasticNetLogisticTrainer.getTerminator().setMaxIteration(this.binaryUpdatesPerIter);
    elasticNetLogisticTrainer.optimize();
    if (logger.isDebugEnabled()) {
        logger.debug("time spent on updating component " + component + " label " + label + " = " + stopWatch);
    }
}

Example 2 with ElasticNetLogisticTrainer

use of edu.neu.ccs.pyramid.classification.logistic_regression.ElasticNetLogisticTrainer in project pyramid by cheng-li.

the class CBMUtilityOptimizer method updateBinaryLogisticRegressionEL.

private void updateBinaryLogisticRegressionEL(int componentIndex, int labelIndex) {
    ElasticNetLogisticTrainer elasticNetLogisticTrainer = new ElasticNetLogisticTrainer.Builder((LogisticRegression) cbm.binaryClassifiers[componentIndex][labelIndex], dataSet, 2, binaryTargetsDistributions[labelIndex], gammasT[componentIndex]).setRegularization(regularizationBinary).setL1Ratio(l1RatioBinary).setLineSearch(lineSearch).build();
    //TODO: maximum iterations
    elasticNetLogisticTrainer.getTerminator().setMaxIteration(10);
    elasticNetLogisticTrainer.optimize();
}

Example 3 with ElasticNetLogisticTrainer

use of edu.neu.ccs.pyramid.classification.logistic_regression.ElasticNetLogisticTrainer in project pyramid by cheng-li.

the class CBMUtilityOptimizer method updateMultiClassEL.

private void updateMultiClassEL() {
    ElasticNetLogisticTrainer elasticNetLogisticTrainer = new ElasticNetLogisticTrainer.Builder((LogisticRegression) cbm.multiClassClassifier, dataSet, cbm.multiClassClassifier.getNumClasses(), gammas).setRegularization(regularizationMultiClass).setL1Ratio(l1RatioMultiClass).setLineSearch(lineSearch).build();
    // TODO: maximum iterations
    elasticNetLogisticTrainer.getTerminator().setMaxIteration(10);
    elasticNetLogisticTrainer.optimize();
}

Example 4 with ElasticNetLogisticTrainer

use of edu.neu.ccs.pyramid.classification.logistic_regression.ElasticNetLogisticTrainer in project pyramid by cheng-li.

the class SparkCBMOptimizer method updateMultiClassEL.

private void updateMultiClassEL() {
    ElasticNetLogisticTrainer elasticNetLogisticTrainer = new ElasticNetLogisticTrainer.Builder((LogisticRegression) cbm.multiClassClassifier, dataSet, cbm.multiClassClassifier.getNumClasses(), gammas).setRegularization(regularizationMultiClass).setL1Ratio(l1RatioMultiClass).setLineSearch(lineSearch).build();
    // TODO: maximum iterations
    elasticNetLogisticTrainer.getTerminator().setMaxIteration(15);
    elasticNetLogisticTrainer.optimize();
}

Example 5 with ElasticNetLogisticTrainer

use of edu.neu.ccs.pyramid.classification.logistic_regression.ElasticNetLogisticTrainer in project pyramid by cheng-li.

the class PlattScaling method fitClassK.

private static LogisticRegression fitClassK(double[] scores, int[] labels) {
    ClfDataSet dataSet = ClfDataSetBuilder.getBuilder().numClasses(2).numDataPoints(scores.length).numFeatures(1).dense(true).missingValue(false).build();
    for (int i = 0; i < scores.length; i++) {
        dataSet.setFeatureValue(i, 0, scores[i]);
        dataSet.setLabel(i, labels[i]);
    }
    LogisticRegression logisticRegression = new LogisticRegression(2, dataSet.getNumFeatures());
    ElasticNetLogisticTrainer trainer = ElasticNetLogisticTrainer.newBuilder(logisticRegression, dataSet).setRegularization(1.0E-9).setL1Ratio(0).build();
    trainer.optimize();
    return logisticRegression;
}