Examples with MeanVariance de.lmu.ifi.dbs.elki.math.MeanVariance used on opensource projects

Example 46 with MeanVariance

use of de.lmu.ifi.dbs.elki.math.MeanVariance in project elki by elki-project.

the class ClusterContingencyTable method averageSymmetricGini.

/**
 * Compute the average Gini for each cluster (in both clusterings -
 * symmetric).
 *
 * @return Mean and variance of Gini
 */
public MeanVariance averageSymmetricGini() {
    MeanVariance mv = new MeanVariance();
    for (int i1 = 0; i1 < size1; i1++) {
        double purity = 0.0;
        if (contingency[i1][size2] > 0) {
            // sum, as double.
            final double cs = contingency[i1][size2];
            for (int i2 = 0; i2 < size2; i2++) {
                double rel = contingency[i1][i2] / cs;
                purity += rel * rel;
            }
            mv.put(purity, cs);
        }
    }
    for (int i2 = 0; i2 < size2; i2++) {
        double purity = 0.0;
        if (contingency[size1][i2] > 0) {
            // sum, as double.
            final double cs = contingency[size1][i2];
            for (int i1 = 0; i1 < size1; i1++) {
                double rel = contingency[i1][i2] / cs;
                purity += rel * rel;
            }
            mv.put(purity, cs);
        }
    }
    return mv;
}

Example 47 with MeanVariance

use of de.lmu.ifi.dbs.elki.math.MeanVariance in project elki by elki-project.

the class HeDESNormalizationOutlierScaling method prepare.

@Override
public <A> void prepare(A array, NumberArrayAdapter<?, A> adapter) {
    MeanVariance mv = new MeanVariance();
    DoubleMinMax minmax = new DoubleMinMax();
    final int size = adapter.size(array);
    for (int i = 0; i < size; i++) {
        double val = adapter.getDouble(array, i);
        if (!Double.isNaN(val) && !Double.isInfinite(val)) {
            mv.put(val);
            minmax.put(val);
        }
    }
    mean = mv.getMean();
    stddev = mv.getSampleStddev();
    scaledmax = getScaled(minmax.getMax());
    scaledmin = getScaled(minmax.getMin());
}

Example 48 with MeanVariance

use of de.lmu.ifi.dbs.elki.math.MeanVariance in project elki by elki-project.

the class HeDESNormalizationOutlierScaling method prepare.

@Override
public void prepare(OutlierResult or) {
    MeanVariance mv = new MeanVariance();
    DoubleMinMax minmax = new DoubleMinMax();
    DoubleRelation scores = or.getScores();
    for (DBIDIter id = scores.iterDBIDs(); id.valid(); id.advance()) {
        double val = scores.doubleValue(id);
        if (!Double.isNaN(val) && !Double.isInfinite(val)) {
            mv.put(val);
            minmax.put(val);
        }
    }
    mean = mv.getMean();
    stddev = mv.getSampleStddev();
    scaledmax = getScaled(minmax.getMax());
    scaledmin = getScaled(minmax.getMin());
}

Example 49 with MeanVariance

use of de.lmu.ifi.dbs.elki.math.MeanVariance in project elki by elki-project.

the class MinusLogGammaScaling method prepare.

@Override
public void prepare(OutlierResult or) {
    meta = or.getOutlierMeta();
    // Determine Minimum and Maximum.
    DoubleMinMax mm = new DoubleMinMax();
    DoubleRelation scores = or.getScores();
    for (DBIDIter id = scores.iterDBIDs(); id.valid(); id.advance()) {
        double score = scores.doubleValue(id);
        if (!Double.isNaN(score) && !Double.isInfinite(score)) {
            mm.put(score);
        }
    }
    max = mm.getMax();
    mlogmax = -FastMath.log(mm.getMin() / max);
    // with the prescaling, do Gamma Scaling.
    MeanVariance mv = new MeanVariance();
    for (DBIDIter id = scores.iterDBIDs(); id.valid(); id.advance()) {
        double score = scores.doubleValue(id);
        score = preScale(score);
        if (!Double.isNaN(score) && !Double.isInfinite(score)) {
            mv.put(score);
        }
    }
    final double mean = mv.getMean();
    final double var = mv.getSampleVariance();
    k = (mean * mean) / var;
    theta = var / mean;
    atmean = GammaDistribution.regularizedGammaP(k, mean / theta);
// logger.warning("Mean:"+mean+" Var:"+var+" Theta: "+theta+" k: "+k+"
// valatmean"+atmean);
}

Example 50 with MeanVariance

use of de.lmu.ifi.dbs.elki.math.MeanVariance in project elki by elki-project.

the class OutlierGammaScaling method prepare.

@Override
public <A> void prepare(A array, NumberArrayAdapter<?, A> adapter) {
    MeanVariance mv = new MeanVariance();
    final int size = adapter.size(array);
    for (int i = 0; i < size; i++) {
        double score = adapter.getDouble(array, i);
        score = preScale(score);
        if (!Double.isNaN(score) && !Double.isInfinite(score)) {
            mv.put(score);
        }
    }
    final double mean = mv.getMean();
    final double var = mv.getSampleVariance();
    k = (mean * mean) / var;
    theta = var / mean;
    atmean = GammaDistribution.regularizedGammaP(k, mean / theta);
// logger.warning("Mean:"+mean+" Var:"+var+" Theta: "+theta+" k: "+k+" valatmean"+atmean);
}