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

Example 1 with ClassProbability

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

the class LogisticRegressionInspector method analyzePrediction.

public static PredictionAnalysis analyzePrediction(LogisticRegression logisticRegression, ClfDataSet dataSet, int dataPointIndex, int limit) {
    PredictionAnalysis predictionAnalysis = new PredictionAnalysis();
    IdTranslator idTranslator = dataSet.getIdTranslator();
    LabelTranslator labelTranslator = dataSet.getLabelTranslator();
    predictionAnalysis.setInternalId(dataPointIndex).setId(idTranslator.toExtId(dataPointIndex)).setInternalLabel(dataSet.getLabels()[dataPointIndex]).setLabel(labelTranslator.toExtLabel(dataSet.getLabels()[dataPointIndex]));
    int prediction = logisticRegression.predict(dataSet.getRow(dataPointIndex));
    predictionAnalysis.setInternalPrediction(prediction);
    predictionAnalysis.setPrediction(labelTranslator.toExtLabel(prediction));
    double[] probs = logisticRegression.predictClassProbs(dataSet.getRow(dataPointIndex));
    List<ClassProbability> classProbabilities = new ArrayList<>();
    for (int k = 0; k < probs.length; k++) {
        ClassProbability classProbability = new ClassProbability(k, labelTranslator.toExtLabel(k), probs[k]);
        classProbabilities.add(classProbability);
    }
    predictionAnalysis.setClassProbabilities(classProbabilities);
    List<ClassScoreCalculation> classScoreCalculations = new ArrayList<>();
    for (int k = 0; k < probs.length; k++) {
        ClassScoreCalculation classScoreCalculation = decisionProcess(logisticRegression, labelTranslator, dataSet.getRow(dataPointIndex), k, limit);
        classScoreCalculations.add(classScoreCalculation);
    }
    predictionAnalysis.setClassScoreCalculations(classScoreCalculations);
    return predictionAnalysis;
}

Example 2 with ClassProbability

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

the class LKBInspector method analyzePrediction.

//todo  speed up
public static PredictionAnalysis analyzePrediction(LKBoost boosting, ClfDataSet dataSet, int dataPointIndex, int limit) {
    PredictionAnalysis predictionAnalysis = new PredictionAnalysis();
    IdTranslator idTranslator = dataSet.getIdTranslator();
    LabelTranslator labelTranslator = dataSet.getLabelTranslator();
    predictionAnalysis.setInternalId(dataPointIndex).setId(idTranslator.toExtId(dataPointIndex)).setInternalLabel(dataSet.getLabels()[dataPointIndex]).setLabel(labelTranslator.toExtLabel(dataSet.getLabels()[dataPointIndex]));
    int prediction = boosting.predict(dataSet.getRow(dataPointIndex));
    predictionAnalysis.setInternalPrediction(prediction);
    predictionAnalysis.setPrediction(labelTranslator.toExtLabel(prediction));
    double[] probs = boosting.predictClassProbs(dataSet.getRow(dataPointIndex));
    List<ClassProbability> classProbabilities = new ArrayList<>();
    for (int k = 0; k < probs.length; k++) {
        ClassProbability classProbability = new ClassProbability(k, labelTranslator.toExtLabel(k), probs[k]);
        classProbabilities.add(classProbability);
    }
    predictionAnalysis.setClassProbabilities(classProbabilities);
    List<ClassScoreCalculation> classScoreCalculations = new ArrayList<>();
    for (int k = 0; k < probs.length; k++) {
        ClassScoreCalculation classScoreCalculation = decisionProcess(boosting, labelTranslator, dataSet.getRow(dataPointIndex), k, limit);
        classScoreCalculations.add(classScoreCalculation);
    }
    predictionAnalysis.setClassScoreCalculations(classScoreCalculations);
    return predictionAnalysis;
}