SampleClassificationProblem.java

package edu.cmu.minorthird.text.learn;

import java.util.Iterator;

import edu.cmu.minorthird.classify.SampleDatasets;
import edu.cmu.minorthird.text.BasicTextBase;
import edu.cmu.minorthird.text.BasicTextLabels;
import edu.cmu.minorthird.text.Span;
import edu.cmu.minorthird.text.TextLabels;
import edu.cmu.minorthird.text.TextLabelsLoader;

/**
 * Some sample inputs to facilitate testing.
 * 
 * @author William Cohen
 */

public class SampleClassificationProblem{

//	static private Logger log=Logger.getLogger(SampleClassificationProblem.class);

//	static private String[] posTrain=SampleDatasets.posTrain;

//	static private String[] negTrain=SampleDatasets.negTrain;

//	static private String[] posTest=SampleDatasets.posTest;

//	static private String[] negTest=SampleDatasets.negTest;

	static public TextLabels trainLabels(){
		return makeLabels(SampleDatasets.posTrain,SampleDatasets.negTest);
	}

	static public TextLabels testLabels(){
		return makeLabels(SampleDatasets.posTest,SampleDatasets.negTest);
	}

	static public TextLabels unlabeled(){
		String[] pos=SampleDatasets.posTest;
		String[] neg=SampleDatasets.negTest;

		BasicTextBase base=new BasicTextBase();
		for(int i=0;i<pos.length;i++){
			base.loadDocument("pos."+i,pos[i]);
		}
		for(int i=0;i<neg.length;i++){
			base.loadDocument("neg."+i,neg[i]);
		}
		BasicTextLabels labels=new BasicTextLabels(base);

		return labels;

	}

	static private TextLabels makeLabels(String[] pos,String[] neg){
		BasicTextBase base=new BasicTextBase();
		for(int i=0;i<pos.length;i++){
			base.loadDocument("pos."+i,pos[i]);
		}
		for(int i=0;i<neg.length;i++){
			base.loadDocument("neg."+i,neg[i]);
		}
		BasicTextLabels labels=new BasicTextLabels(base);
		for(Iterator<Span> i=base.documentSpanIterator();i.hasNext();){
			Span s=i.next();
			if(s.getDocumentId().startsWith("pos")){
				labels.addToType(s,"fun");
			}
		}
		new TextLabelsLoader().closeLabels(labels,TextLabelsLoader.CLOSE_ALL_TYPES);
		return labels;
	}
}