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The MEKA project provides an open source implementation of methods for multi-label classification and evaluation. It is based on the WEKA Machine Learning Toolkit. Several benchmark methods are also included, as well as the pruned sets and classifier chains methods, other methods from the scientific literature, and a wrapper to the MULAN framework.

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/*
 *   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 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 General Public License for more details.
 *
 *   You should have received a copy of the GNU General Public License
 *   along with this program.  If not, see .
 */

package meka.classifiers.multilabel;

import weka.core.Instances;

/**
 *  SemisupervisedClassifier.java - An Interface for Multilabel Semisupervised Classifiers.
 *  This is an interface for multi-label semisupervised classificatation, i.e., training on a partially labelled dataset. 

 *  For classifiers implementing this interface, the method introduceUnlabelledData(unlabeledInstances) will be called prior to buildClassifier(trainingInstances). 

 *  As of writing this comment, the unlabelled data comes only from the test data -- there is not yet any option for setting a seperate sete of unlabelled data (although this is planned for future versions).
 *
 * 	@author 	Jesse Read
 * 	@version	September 2015
 */

public interface SemisupervisedClassifier
		extends MultiLabelClassifier {

	/**
	 *  Set Unlabelled Data - provide unlabelled data prior to calling buildClassifier(Instances).
	 *  @param	unlabeledInstances	Instances for which the true class labels are not available for each instance.
	 */
	void introduceUnlabelledData(Instances unlabeledInstances);
}