Commit c85f7508 authored by Antoine RICHARD's avatar Antoine RICHARD
Browse files

add learners

parent 85b608c9
......@@ -25,6 +25,8 @@ import java.util.Arrays;
import java.util.HashMap;
import mulan.classifier.MultiLabelLearnerBase;
import mulan.classifier.meta.RAkEL;
import mulan.classifier.neural.BPMLL;
import mulan.classifier.lazy.MLkNN;
import mulan.classifier.transformation.LabelPowerset;
import org.apache.logging.log4j.LogManager;
import org.apache.logging.log4j.Logger;
......@@ -34,6 +36,7 @@ import mulan.evaluation.MultipleEvaluation;
import weka.classifiers.bayes.NaiveBayes;
import weka.classifiers.rules.JRip;
import weka.classifiers.trees.J48;
import weka.classifiers.functions.SMO;
import weka.core.Utils;
/**
......@@ -138,23 +141,14 @@ public class App
// Init Learners
HashMap<String, MultiLabelLearnerBase> learners = new HashMap<>();
//learners.put("FuzzyBayes", new FuzzyBayes());
//learners.put("HistBayes", new HistBayes());
//learners.put("RAkEL+NaiveBayes", new RAkEL(new LabelPowerset(new NaiveBayes()))); // Bayes Net
//learners.put("RAkEL+C4.5", new RAkEL(new LabelPowerset(new J48()))); // Decision Tree
//learners.put("RAkEL+Ripper", new RAkEL(new LabelPowerset(new JRip()))); // Rules
//learners.put("MLkNN", new MLkNN()); // k-Nearest Neighboors
learners.put("FuzzyBayes", new FuzzyBayes());
learners.put("HistBayes", new HistBayes());
learners.put("RAkEL+NaiveBayes", new RAkEL(new LabelPowerset(new NaiveBayes()))); // Bayes Net
learners.put("RAkEL+C4.5", new RAkEL(new LabelPowerset(new J48()))); // Decision Tree
learners.put("RAkEL+Ripper", new RAkEL(new LabelPowerset(new JRip()))); // Rules
learners.put("BPMLL", new BPMLL()); // neural network
//learners.put("RAkEL+LMT", new RAkEL(new LabelPowerset(new LMT()))); // Decision Tree
//learners.put("RAkEL+PART", new RAkEL(new LabelPowerset(new PART()))); // DT + Rules
//learners.put("RAkEL+KStar", new RAkEL(new LabelPowerset(new KStar()))); // instance based
//learners.put("RAkEL+SMO", new RAkEL(new LabelPowerset(new SMO()))); // SVM
learners.put("MLkNN", new MLkNN()); // k-Nearest Neighboors
learners.put("RAkEL", new RAkEL(new LabelPowerset(new SMO()))); // SVM
// For each selected learner
......
#!/usr/bin/env sh
cd api
mvn clean package
if [ $? -ne 0 ]; then
exit
fi
java -cp target/api-1.0-SNAPSHOT.jar com.lamsade.App
if [ $? -ne 0 ]; then
exit
fi
cd ../
./renderer.R
if [ $? -ne 0 ]; then
exit
fi
xdg-open experiment.html &
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