/*
* RapidMiner
*
* Copyright (C) 2001-2014 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.igss.utility;
import com.rapidminer.operator.learner.igss.hypothesis.Hypothesis;
/** Interface for all utility functions.
*
* @author Dirk Dach
*/
public interface Utility {
public static final String[] UTILITY_TYPES={"accuracy","linear","squared","binomial","wracc"};
public static final int FIRST_TYPE_INDEX=0;
public static final int TYPE_ACCURACY=0;
public static final int TYPE_LINEAR=1;
public static final int TYPE_SQUARED=2;
public static final int TYPE_BINOMIAL=3;
public static final int TYPE_WRACC=4;
public static final int LAST_TYPE_INDEX=4;
/** Calculates the utility for the given number of examples,positive examples and hypothesis*/
public double utility(double totalWeight, double totalPositiveWeight, Hypothesis hypo);
/** Calculates the M-value needed for the GSS algorithm. */
public double calculateM (double delta, double epsilon);
/** Calculates the the unspecific confidence intervall.
* Uses Chernoff bounds if the number of random experiments is too small and normal approximatione otherwise. */
public double confidenceIntervall (double totalWeight, double delta);
/** Calculates the the confidence intervall for a specific hypothesis.
* Uses Chernoff bounds if the number of random experiments is too small and normal approximation otherwise. */
public double confidenceIntervall (double totalWeight, double totalPositiveWeight, Hypothesis hypo, double delta);
/** Returns an upper bound for the utility of refinements for the given hypothesis. */
public double getUpperBound(double totalWeight, double totalPositiveWeight, Hypothesis hypo, double delta);
}