package com.jgaap.classifiers;
import java.util.HashMap;
import java.util.List;
import weka.classifiers.Classifier;
import weka.classifiers.meta.ClassificationViaRegression;
import com.jgaap.generics.AnalyzeException;
import com.jgaap.generics.WEKAAnalysisDriver;
import com.jgaap.util.Document;
public class WEKALinearRegression extends WEKAAnalysisDriver {
@Override
public String displayName() {
return "WEKA Linear Regression";
}
@Override
public String tooltipText() {
return "Linear Regression, Courtesy of WEKA";
}
@Override
public boolean showInGUI() {
return true;
}
public Classifier getClassifier() {
ClassificationViaRegression c = new ClassificationViaRegression();
c.setClassifier(new weka.classifiers.functions.LinearRegression());
return (Classifier)c;
}
public void testRequirements(List<Document> knownList) throws AnalyzeException{
//Linear Regression requires at least two documents per author
//Make a "list" of the number of documents per author
HashMap<String, Integer> docsPerAuthor = new HashMap<String, Integer>();
for(Document e : knownList){
if(docsPerAuthor.containsKey(e.getAuthor())){
docsPerAuthor.put(e.getAuthor(), docsPerAuthor.get(e.getAuthor())+1);
}else{
docsPerAuthor.put(e.getAuthor(),1);
}
}
//Test that each author has at least two documents. If not, throw a
// new exception.
for(String s : docsPerAuthor.keySet()){
if(docsPerAuthor.get(s) < 2){
throw new AnalyzeException("Weka Linear Regression classifier requires at "
+"least two documents per author.\nAuthor '"+s+"' has only "
+docsPerAuthor.get(s)+" documents.");
}
}
}
}