/**
* 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.df.split;
import java.util.Random;
import org.apache.mahout.common.MahoutTestCase;
import org.apache.mahout.common.RandomUtils;
import org.apache.mahout.classifier.df.data.Data;
import org.apache.mahout.classifier.df.data.Utils;
import org.junit.Test;
public final class OptIgSplitTest extends MahoutTestCase {
private static final int NUM_ATTRIBUTES = 20;
private static final int NUM_INSTANCES = 100;
@Test
public void testComputeSplit() throws Exception {
IgSplit ref = new DefaultIgSplit();
IgSplit opt = new OptIgSplit();
Random rng = RandomUtils.getRandom();
Data data = Utils.randomData(rng, NUM_ATTRIBUTES, false, NUM_INSTANCES);
for (int nloop = 0; nloop < 100; nloop++) {
int attr = rng.nextInt(data.getDataset().nbAttributes());
// System.out.println("IsNumerical: " + data.dataset.isNumerical(attr));
Split expected = ref.computeSplit(data, attr);
Split actual = opt.computeSplit(data, attr);
assertEquals(expected.getIg(), actual.getIg(), EPSILON);
assertEquals(expected.getSplit(), actual.getSplit(), EPSILON);
}
}
}