/**
* Copyright (C) 2001-2017 by RapidMiner and the contributors
*
* Complete list of developers available at our web site:
*
* http://rapidminer.com
*
* This program is free software: you can redistribute it and/or modify it under the terms of the
* GNU Affero General Public License as published by the Free Software Foundation, either version 3
* of the License, or (at your option) any later version.
*
* This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without
* even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
* Affero General Public License for more details.
*
* You should have received a copy of the GNU Affero General Public License along with this program.
* If not, see http://www.gnu.org/licenses/.
*/
package com.rapidminer.operator.learner.tree.criterions;
import static com.rapidminer.operator.learner.tree.AbstractParallelTreeLearner.CRITERIA_CLASSES;
import static com.rapidminer.operator.learner.tree.AbstractParallelTreeLearner.CRITERIA_NAMES;
import static com.rapidminer.operator.learner.tree.AbstractParallelTreeLearner.PARAMETER_CRITERION;
import com.rapidminer.operator.OperatorException;
import com.rapidminer.operator.learner.tree.ColumnExampleTable;
import com.rapidminer.operator.learner.tree.ColumnFrequencyCalculator;
import com.rapidminer.operator.learner.tree.MinimalGainHandler;
import com.rapidminer.parameter.ParameterHandler;
import com.rapidminer.tools.Tools;
/**
* This criterion class can be used for the incremental calculation of benefits.
*
* @author Sebastian Land, Gisa Schaefer
*/
public abstract class AbstractColumnCriterion implements ColumnCriterion {
@Override
public boolean supportsIncrementalCalculation() {
return false;
}
@Override
public WeightDistribution startIncrementalCalculation(ColumnExampleTable columnTable, int[] selection,
int numericalAttributeNumber) {
return new WeightDistribution(columnTable, selection, numericalAttributeNumber);
}
@Override
public void updateWeightDistribution(ColumnExampleTable columnTable, int row, WeightDistribution distribution) {
double weight = 1;
if (columnTable.getWeight() != null) {
weight = columnTable.getWeightColumn()[row];
}
int label = columnTable.getLabelColumn()[row];
distribution.increment(label, weight);
}
@Override
public double getNominalBenefit(ColumnExampleTable columnTable, int[] selection, int attributeNumber) {
double[][] weightCounts = ColumnFrequencyCalculator.getNominalWeightCounts(columnTable, selection, attributeNumber);
return getBenefit(weightCounts);
}
@Override
public double getNumericalBenefit(ColumnExampleTable columnTable, int[] selection, int attributeNumber, double splitValue) {
double[][] weightCounts = ColumnFrequencyCalculator.getNumericalWeightCounts(columnTable, selection,
attributeNumber, splitValue);
return getBenefit(weightCounts);
}
/**
* This method returns the criterion specified by the respective parameters.
*/
public static ColumnCriterion createColumnCriterion(ParameterHandler handler, double minimalGain)
throws OperatorException {
String criterionName = handler.getParameterAsString(PARAMETER_CRITERION);
Class<?> criterionClass = null;
for (int i = 0; i < CRITERIA_NAMES.length; i++) {
if (CRITERIA_NAMES[i].equals(criterionName)) {
criterionClass = CRITERIA_CLASSES[i];
}
}
if (criterionClass == null && criterionName != null) {
try {
criterionClass = Tools.classForName(criterionName);
} catch (ClassNotFoundException e) {
throw new OperatorException("Cannot find criterion '" + criterionName
+ "' and cannot instantiate a class with this name.");
}
}
if (criterionClass != null) {
try {
ColumnCriterion criterion = (ColumnCriterion) criterionClass.newInstance();
if (criterion instanceof MinimalGainHandler) {
((MinimalGainHandler) criterion).setMinimalGain(minimalGain);
}
return criterion;
} catch (InstantiationException e) {
throw new OperatorException("Cannot instantiate criterion class '" + criterionClass.getName() + "'.");
} catch (IllegalAccessException e) {
throw new OperatorException("Cannot access criterion class '" + criterionClass.getName() + "'.");
}
} else {
throw new OperatorException("No relevance criterion defined.");
}
}
}