/*
* Clusterer.java
* Copyright (C) 2009 University of Waikato, Hamilton, New Zealand
* @author Albert Bifet (abifet@cs.waikato.ac.nz)
*
* 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.
*/
package tr.gov.ulakbim.jDenetX.clusterers;
import tr.gov.ulakbim.jDenetX.MOAObject;
import tr.gov.ulakbim.jDenetX.cluster.Clustering;
import tr.gov.ulakbim.jDenetX.core.InstancesHeader;
import tr.gov.ulakbim.jDenetX.core.Measurement;
import tr.gov.ulakbim.jDenetX.gui.AWTRenderable;
import tr.gov.ulakbim.jDenetX.options.OptionHandler;
import weka.core.Instance;
public interface Clusterer extends MOAObject, OptionHandler, AWTRenderable {
public void setModelContext(InstancesHeader ih);
public InstancesHeader getModelContext();
public boolean isRandomizable();
public void setRandomSeed(int s);
public boolean trainingHasStarted();
public double trainingWeightSeenByModel();
public void resetLearning();
public void trainOnInstance(Instance inst);
public double[] getVotesForInstance(Instance inst);
//public boolean correctlyClassifies(Instance inst);
public Measurement[] getModelMeasurements();
public Clusterer[] getSubClusterers();
public Clusterer copy();
public Clustering getClusteringResult();
public boolean implementsMicroClusterer();
public Clustering getMicroClusteringResult();
}