/*
* 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., 675 Mass Ave, Cambridge, MA 02139, USA.
*/
/*
* MultiClassAttributeEvaluator.java
* Copyright (C) 2009-2010 Aristotle University of Thessaloniki, Thessaloniki, Greece
*/
package mulan.dimensionalityReduction;
import java.util.logging.Level;
import java.util.logging.Logger;
import mulan.data.MultiLabelInstances;
import mulan.transformations.multiclass.MultiClassTransformation;
import weka.attributeSelection.ASEvaluation;
import weka.attributeSelection.AttributeEvaluator;
import weka.core.Instances;
/**
* Performs attribute evaluation using single-label transformations. For
* more information, see <br/>
* <br/>
* Chen, W., Yan, J., Zhang, B., Chen, Z., and Yang, Q. (2007).
* Document transformation for multi-label feature selection in text categorization.
* In 7th IEEE International Conference on Data Mining (ICDM'07), pages 451-456.
* </p>
*
* BibTeX:
*
* <pre>
* @inproceedings{chen+etal:2007,
* author = {Chen, Weizhu and Yan, Jun and Zhang, Benyu and Chen, Zheng and Yang, Qiang},
* booktitle = {Proc. 7th IEEE International Conference on Data Mining (ICDM'07)},
* pages = {451--456},
* title = {Document Transformation for Multi-label Feature Selection in Text Categorization},
* year = {2007}
* }
* </pre>
*
* @author Grigorios Tsoumakas
* @version 10 August 2010
*/
public class MultiClassAttributeEvaluator extends ASEvaluation implements AttributeEvaluator {
/** The single-label attribute evaluator to use underneath */
private ASEvaluation baseAttributeEvaluator;
/** Constructor that uses an evaluator on a multi-label dataset using a transformation
* @param x
* @param dt
* @param mlData */
public MultiClassAttributeEvaluator(ASEvaluation x, MultiClassTransformation dt, MultiLabelInstances mlData) {
baseAttributeEvaluator = x;
Instances data;
try {
data = dt.transformInstances(mlData);
((ASEvaluation) baseAttributeEvaluator).buildEvaluator(data);
} catch (Exception ex) {
Logger.getLogger(MultiClassAttributeEvaluator.class.getName()).log(Level.SEVERE, null, ex);
}
}
@Override
public double evaluateAttribute(int attribute) throws Exception {
return ((AttributeEvaluator) baseAttributeEvaluator).evaluateAttribute(attribute);
}
@Override
public void buildEvaluator(Instances arg0) throws Exception {
throw new UnsupportedOperationException("Not supported yet.");
}
}