/* * 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()); } }