Java tutorial
/* * 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.Set; import mlda.base.MLDataMetric; import mulan.data.MultiLabelInstances; import weka.core.Attribute; import weka.core.Instances; /** * Class implementing the Mean of standard deviation of numeric attributes * * @author Jose Maria Moyano Murillo */ public class MeanStdvNumericAttributes extends MLDataMetric { /** * Constructor */ public MeanStdvNumericAttributes() { super("Mean of standard deviation of 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) { double mean = 0; int nNumeric = 0; Instances instances = mlData.getDataSet(); Set<Attribute> attributeSet = mlData.getFeatureAttributes(); for (Attribute att : attributeSet) { if (att.isNumeric()) { nNumeric++; mean += Math.sqrt(instances.variance(att)); } } if (nNumeric > 0) { this.value = mean / nNumeric; } else { this.value = Double.NaN; } //this.value = mean; return value; } }