mlda.attributes.AvgAbsoluteCorrelationBetweenNumericAttributes.java Source code

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Here is the source code for mlda.attributes.AvgAbsoluteCorrelationBetweenNumericAttributes.java

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/*
 * This file is part of the MLDA.
 *
 * (c)  Jose Maria Moyano Murillo
 *      Eva Lucrecia Gibaja Galindo
 *      Sebastian Ventura Soto <sventura@uco.es>
 *
 * For the full copyright and license information, please view the LICENSE
 * file that was distributed with this source code.
 */

package mlda.attributes;

import java.util.Vector;

import mlda.base.MLDataMetric;
import mulan.data.MultiLabelInstances;
import weka.core.Instances;
import weka.core.Utils;

/**
* Class implementing the Average absolute correlation between numeric attributes
*
* @author Jose Maria Moyano Murillo
*/
public class AvgAbsoluteCorrelationBetweenNumericAttributes extends MLDataMetric {

    /**
     * Constructor
     */
    public AvgAbsoluteCorrelationBetweenNumericAttributes() {
        super("Average absolute correlation between numeric attributes");
    }

    /**
     * Calculate metric value
     * 
     * @param mlData Multi-label dataset to which calculate the metric
     * @return Value of the metric
     */
    public double calculate(MultiLabelInstances mlData) {
        Instances instances = mlData.getDataSet();

        int numInstances = mlData.getNumInstances();

        double res = 0.0;
        int count = 0;

        int[] featureIndices = mlData.getFeatureIndices();

        Vector<Integer> numericFeatureIndices = new Vector<>();
        for (int fIndex : featureIndices) {
            if (instances.attribute(fIndex).isNumeric()) {
                numericFeatureIndices.add(fIndex);
            }
        }

        if (numericFeatureIndices.size() <= 0) {
            return Double.NaN;
        }

        double[][] attributesToDoubleArray = new double[numericFeatureIndices.size()][numInstances];
        for (int fIndex : numericFeatureIndices) {
            attributesToDoubleArray[fIndex] = instances.attributeToDoubleArray(fIndex);
        }

        for (int fIndex1 : numericFeatureIndices) {
            for (int fIndex2 = fIndex1 + 1; fIndex2 < numericFeatureIndices.size(); fIndex2++) {
                count++;
                res += Utils.correlation(attributesToDoubleArray[fIndex1], attributesToDoubleArray[fIndex2],
                        numInstances);
            }
        }

        if (count > 0) {
            this.value = res / count;
        } else {
            this.value = Double.NaN;
        }

        //this.value = res/count;
        return value;
    }

}