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* 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.cf.taste.impl.similarity;
import java.util.Collection;
import org.apache.mahout.cf.taste.common.Refreshable;
import org.apache.mahout.cf.taste.common.Weighting;
import org.apache.mahout.cf.taste.model.DataModel;
import org.apache.mahout.cf.taste.similarity.ItemSimilarity;
import org.apache.mahout.cf.taste.similarity.PreferenceInferrer;
import org.apache.mahout.cf.taste.similarity.UserSimilarity;
import org.junit.Test;
/** <p>Tests {@link PearsonCorrelationSimilarity}.</p> */
public final class PearsonCorrelationSimilarityTest extends SimilarityTestCase {
@Test
public void testFullCorrelation1() throws Exception {
DataModel dataModel = getDataModel(
new long[] {1, 2},
new Double[][] {
{3.0, -2.0},
{3.0, -2.0},
});
double correlation = new PearsonCorrelationSimilarity(dataModel).userSimilarity(1, 2);
assertCorrelationEquals(1.0, correlation);
}
@Test
public void testFullCorrelation1Weighted() throws Exception {
DataModel dataModel = getDataModel(
new long[] {1, 2},
new Double[][] {
{3.0, -2.0},
{3.0, -2.0},
});
double correlation = new PearsonCorrelationSimilarity(dataModel, Weighting.WEIGHTED).userSimilarity(1, 2);
assertCorrelationEquals(1.0, correlation);
}
@Test
public void testFullCorrelation2() throws Exception {
DataModel dataModel = getDataModel(
new long[] {1, 2},
new Double[][] {
{3.0, 3.0},
{3.0, 3.0},
});
double correlation = new PearsonCorrelationSimilarity(dataModel).userSimilarity(1, 2);
// Yeah, undefined in this case
assertTrue(Double.isNaN(correlation));
}
@Test
public void testNoCorrelation1() throws Exception {
DataModel dataModel = getDataModel(
new long[] {1, 2},
new Double[][] {
{3.0, -2.0},
{-3.0, 2.0},
});
double correlation = new PearsonCorrelationSimilarity(dataModel).userSimilarity(1, 2);
assertCorrelationEquals(-1.0, correlation);
}
@Test
public void testNoCorrelation1Weighted() throws Exception {
DataModel dataModel = getDataModel(
new long[] {1, 2},
new Double[][] {
{3.0, -2.0},
{-3.0, 2.0},
});
double correlation = new PearsonCorrelationSimilarity(dataModel, Weighting.WEIGHTED).userSimilarity(1, 2);
assertCorrelationEquals(-1.0, correlation);
}
@Test
public void testNoCorrelation2() throws Exception {
DataModel dataModel = getDataModel(
new long[] {1, 2},
new Double[][] {
{null, 1.0, null},
{null, null, 1.0},
});
double correlation = new PearsonCorrelationSimilarity(dataModel).userSimilarity(1, 2);
assertTrue(Double.isNaN(correlation));
}
@Test
public void testNoCorrelation3() throws Exception {
DataModel dataModel = getDataModel(
new long[] {1, 2},
new Double[][] {
{90.0, 80.0, 70.0},
{70.0, 80.0, 90.0},
});
double correlation = new PearsonCorrelationSimilarity(dataModel).userSimilarity(1, 2);
assertCorrelationEquals(-1.0, correlation);
}
@Test
public void testSimple() throws Exception {
DataModel dataModel = getDataModel(
new long[] {1, 2},
new Double[][] {
{1.0, 2.0, 3.0},
{2.0, 5.0, 6.0},
});
double correlation = new PearsonCorrelationSimilarity(dataModel).userSimilarity(1, 2);
assertCorrelationEquals(0.9607689228305227, correlation);
}
@Test
public void testSimpleWeighted() throws Exception {
DataModel dataModel = getDataModel(
new long[] {1, 2},
new Double[][] {
{1.0, 2.0, 3.0},
{2.0, 5.0, 6.0},
});
double correlation = new PearsonCorrelationSimilarity(dataModel, Weighting.WEIGHTED).userSimilarity(1, 2);
assertCorrelationEquals(0.9901922307076306, correlation);
}
@Test
public void testFullItemCorrelation1() throws Exception {
DataModel dataModel = getDataModel(
new long[] {1, 2},
new Double[][] {
{3.0, 3.0},
{-2.0, -2.0},
});
double correlation =
new PearsonCorrelationSimilarity(dataModel).itemSimilarity(0, 1);
assertCorrelationEquals(1.0, correlation);
}
@Test
public void testFullItemCorrelation2() throws Exception {
DataModel dataModel = getDataModel(
new long[] {1, 2},
new Double[][] {
{3.0, 3.0},
{3.0, 3.0},
});
double correlation =
new PearsonCorrelationSimilarity(dataModel).itemSimilarity(0, 1);
// Yeah, undefined in this case
assertTrue(Double.isNaN(correlation));
}
@Test
public void testNoItemCorrelation1() throws Exception {
DataModel dataModel = getDataModel(
new long[] {1, 2},
new Double[][] {
{3.0, -3.0},
{2.0, -2.0},
});
double correlation =
new PearsonCorrelationSimilarity(dataModel).itemSimilarity(0, 1);
assertCorrelationEquals(-1.0, correlation);
}
@Test
public void testNoItemCorrelation2() throws Exception {
DataModel dataModel = getDataModel(
new long[] {1, 2},
new Double[][] {
{null, 1.0, null},
{null, null, 1.0},
});
double correlation =
new PearsonCorrelationSimilarity(dataModel).itemSimilarity(1, 2);
assertTrue(Double.isNaN(correlation));
}
@Test
public void testNoItemCorrelation3() throws Exception {
DataModel dataModel = getDataModel(
new long[] {1, 2, 3},
new Double[][] {
{90.0, 70.0},
{80.0, 80.0},
{70.0, 90.0},
});
double correlation =
new PearsonCorrelationSimilarity(dataModel).itemSimilarity(0, 1);
assertCorrelationEquals(-1.0, correlation);
}
@Test
public void testSimpleItem() throws Exception {
DataModel dataModel = getDataModel(
new long[] {1, 2, 3},
new Double[][] {
{1.0, 2.0},
{2.0, 5.0},
{3.0, 6.0},
});
double correlation =
new PearsonCorrelationSimilarity(dataModel).itemSimilarity(0, 1);
assertCorrelationEquals(0.9607689228305227, correlation);
}
@Test
public void testSimpleItemWeighted() throws Exception {
DataModel dataModel = getDataModel(
new long[] {1, 2, 3},
new Double[][] {
{1.0, 2.0},
{2.0, 5.0},
{3.0, 6.0},
});
ItemSimilarity itemSimilarity = new PearsonCorrelationSimilarity(dataModel, Weighting.WEIGHTED);
double correlation = itemSimilarity.itemSimilarity(0, 1);
assertCorrelationEquals(0.9901922307076306, correlation);
}
@Test
public void testRefresh() throws Exception {
// Make sure this doesn't throw an exception
new PearsonCorrelationSimilarity(getDataModel()).refresh(null);
}
@Test
public void testInferrer() throws Exception {
DataModel dataModel = getDataModel(
new long[] {1, 2},
new Double[][] {
{null, 1.0, 2.0, null, null, 6.0},
{1.0, 8.0, null, 3.0, 4.0, null},
});
UserSimilarity similarity = new PearsonCorrelationSimilarity(dataModel);
similarity.setPreferenceInferrer(new PreferenceInferrer() {
@Override
public float inferPreference(long userID, long itemID) {
return 1.0f;
}
@Override
public void refresh(Collection<Refreshable> alreadyRefreshed) {
}
});
assertEquals(-0.435285750066007, similarity.userSimilarity(1L, 2L), EPSILON);
}
}