/*
* RapidMiner
*
* Copyright (C) 2001-2007 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 General Public License as
* published by the Free Software Foundation; either version 2 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
* General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with this program; if not, write to the Free Software
* Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307
* USA.
*/
package com.rapidminer.operator.postprocessing;
import java.util.List;
import com.rapidminer.example.ExampleSet;
import com.rapidminer.example.set.SplittedExampleSet;
import com.rapidminer.operator.OperatorDescription;
import com.rapidminer.operator.OperatorException;
import com.rapidminer.operator.UserError;
import com.rapidminer.parameter.ParameterType;
import com.rapidminer.parameter.ParameterTypeCategory;
import com.rapidminer.parameter.ParameterTypeInt;
/**
* <p>An operator chain that split an {@link ExampleSet} into two disjunct parts
* and applies the first child operator on the first part and applies the second
* child on the second part and the result of the first child. The total result
* is the result of the second operator.</p>
*
* <p>The input example set will be splitted based on a user defined absolute
* numbers.</p>
*
* @author Peter B. Volk, Ingo Mierswa
* @version $Id: AbsoluteSplitChain.java,v 1.2 2007/06/15 16:58:38 ingomierswa Exp $
*/
public class AbsoluteSplitChain extends AbstractSplitChain {
/** The parameter name for "Defines the sampling type of this operator." */
public static final String PARAMETER_SAMPLING_TYPE = "sampling_type";
/** The parameter name for "Use the given random seed instead of global random numbers (-1: use global)." */
public static final String PARAMETER_LOCAL_RANDOM_SEED = "local_random_seed";
private static final String SPLIT_NAME_TRAIN = "number_training_examples";
private static final String SPLIT_NAME_TEST = "number_test_examples";
public AbsoluteSplitChain(OperatorDescription description) {
super(description);
}
protected SplittedExampleSet createSplittedExampleSet(ExampleSet inputSet) throws OperatorException {
int size = -1;
if (getParameterAsInt(SPLIT_NAME_TEST) == -1) {
if (getParameterAsInt(SPLIT_NAME_TRAIN) == -1) {
throw new UserError(this, 208, SPLIT_NAME_TEST, SPLIT_NAME_TRAIN);
}
size = getParameterAsInt(SPLIT_NAME_TRAIN);
} else {
if (getParameterAsInt(SPLIT_NAME_TRAIN) != -1) {
throw new UserError(this, 209, SPLIT_NAME_TEST, SPLIT_NAME_TRAIN);
}
size = inputSet.size() - getParameterAsInt(SPLIT_NAME_TEST);
}
return new SplittedExampleSet(inputSet,
(double)size / (double)(inputSet.size()),
getParameterAsInt(PARAMETER_SAMPLING_TYPE),
getParameterAsInt(PARAMETER_LOCAL_RANDOM_SEED));
}
public List<ParameterType> getParameterTypes() {
List<ParameterType> types = super.getParameterTypes();
ParameterType type = new ParameterTypeInt(SPLIT_NAME_TRAIN, "Absolute size of the training set. -1 equal to not defined", -1, Integer.MAX_VALUE, -1);
type.setExpert(false);
types.add(type);
type = new ParameterTypeInt(SPLIT_NAME_TEST, "Absolute size of the test set. -1 equal to not defined", -1, Integer.MAX_VALUE, -1);
type.setExpert(false);
types.add(type);
types.add(new ParameterTypeCategory(PARAMETER_SAMPLING_TYPE, "Defines the sampling type of this operator.", SplittedExampleSet.SAMPLING_NAMES, SplittedExampleSet.SHUFFLED_SAMPLING));
types.add(new ParameterTypeInt(PARAMETER_LOCAL_RANDOM_SEED, "Use the given random seed instead of global random numbers (-1: use global).", -1, Integer.MAX_VALUE, -1));
return types;
}
}