/*
* RapidMiner
*
* Copyright (C) 2001-2011 by Rapid-I and the contributors
*
* Complete list of developers available at our web site:
*
* http://rapid-i.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.tools.math;
import com.rapidminer.operator.Operator;
import com.rapidminer.parameter.ParameterType;
import com.rapidminer.parameter.ParameterTypeCategory;
import com.rapidminer.parameter.UndefinedParameterError;
/** Specifies how roc plots are evaluate:
* - first count correct classifications, then count incorrect ones
* - first count incorrect classifications, then count correct ones
* - distribute them evenly.
*
* @author Simon Fischer
*
*/
public enum ROCBias {
PESSIMISTIC,
NEUTRAL,
OPTIMISTIC;
/** Parameter to select the bias type. */
public static final String PARAMETER_NAME_ROC_BIAS = "roc_bias";
public static ROCBias getROCBiasParameter(Operator operator) throws UndefinedParameterError {
return ROCBias.values()[operator.getParameterAsInt(PARAMETER_NAME_ROC_BIAS)];
}
public static ParameterType makeParameterType() {
String[] values = new String[ROCBias.values().length];
for (int i = 0; i < values.length; i++) {
values[i] = ROCBias.values()[i].toString().toLowerCase();
}
return new ParameterTypeCategory(PARAMETER_NAME_ROC_BIAS, "Determines how the ROC (and AUC) are evaluated: Count correct predictions first, last, or alternatingly", values, OPTIMISTIC.ordinal());
}
}