/**
* 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.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());
}
}