/**
* Licensed to the Apache Software Foundation (ASF) under one or more
* contributor license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright ownership.
* The ASF licenses this file to You under the Apache License, Version 2.0
* (the "License"); you may not use this file except in compliance with
* the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package org.apache.mahout.classifier.bayes;
import junit.framework.TestCase;
import org.apache.mahout.classifier.ClassifierResult;
import org.apache.mahout.classifier.bayes.algorithm.CBayesAlgorithm;
import org.apache.mahout.classifier.bayes.common.BayesParameters;
import org.apache.mahout.classifier.bayes.datastore.InMemoryBayesDatastore;
import org.apache.mahout.classifier.bayes.exceptions.InvalidDatastoreException;
import org.apache.mahout.classifier.bayes.interfaces.Algorithm;
import org.apache.mahout.classifier.bayes.model.ClassifierContext;
public class CBayesClassifierTest extends TestCase {
protected Algorithm algorithm;
protected InMemoryBayesDatastore store;
public CBayesClassifierTest(String s) {
super(s);
}
@Override
protected void setUp() throws Exception {
super.setUp();
algorithm = new CBayesAlgorithm();
store = new InMemoryBayesDatastore(new BayesParameters(1));
//String[] labels = new String[]{"a", "b", "c", "d", "e"};
//long[] labelCounts = new long[]{6, 20, 60, 100, 200};
//String[] features = new String[]{"aa", "bb", "cc", "dd", "ee"};
store.setSigma_jSigma_k(500.0);
store.setSumFeatureWeight("aa", 80);
store.setSumFeatureWeight("bb", 21);
store.setSumFeatureWeight("cc", 60);
store.setSumFeatureWeight("dd", 115);
store.setSumFeatureWeight("ee", 100);
store.setSumLabelWeight("a", 100);
store.setSumLabelWeight("b", 100);
store.setSumLabelWeight("c", 100);
store.setSumLabelWeight("d", 100);
store.setSumLabelWeight("e", 100);
store.setThetaNormalizer("a", -100);
store.setThetaNormalizer("b", -100);
store.setThetaNormalizer("c", -100);
store.setThetaNormalizer("d", -100);
store.setThetaNormalizer("e", -100);
store.loadFeatureWeight("aa", "a", 5);
store.loadFeatureWeight("bb", "a", 1);
store.loadFeatureWeight("bb", "b", 20);
store.loadFeatureWeight("cc", "c", 30);
store.loadFeatureWeight("aa", "c", 25);
store.loadFeatureWeight("dd", "c", 5);
store.loadFeatureWeight("dd", "d", 60);
store.loadFeatureWeight("cc", "d", 40);
store.loadFeatureWeight("ee", "e", 100);
store.loadFeatureWeight("aa", "e", 50);
store.loadFeatureWeight("dd", "e", 50);
store.updateVocabCount();
}
public void test() throws InvalidDatastoreException {
ClassifierContext classifier = new ClassifierContext(algorithm, store);
String[] document = {"aa", "ff"};
ClassifierResult result = classifier.classifyDocument( document, "unknown");
assertNotNull("category is null and it shouldn't be", result);
assertEquals(result + " is not equal to e", "e", result.getLabel());
document = new String[]{"ff"};
result = classifier.classifyDocument(document, "unknown");
assertNotNull("category is null and it shouldn't be", result);
assertEquals(result + " is not equal to d", "d", result.getLabel());
document = new String[]{"cc"};
result = classifier.classifyDocument( document, "unknown");
assertNotNull("category is null and it shouldn't be", result);
assertEquals(result + " is not equal to d", "d", result.getLabel());
}
public void testResults() throws Exception {
ClassifierContext classifier = new ClassifierContext(algorithm, store);
String[] document = {"aa", "ff"};
ClassifierResult result = classifier.classifyDocument( document, "unknown");
assertNotNull("category is null and it shouldn't be", result);
System.out.println("Result: " + result);
}
}