/**
* 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.example.kddcup.track1;
import java.io.File;
import java.io.IOException;
import org.apache.commons.cli2.OptionException;
import org.apache.mahout.cf.taste.common.TasteException;
import org.apache.mahout.cf.taste.example.TasteOptionParser;
import org.apache.mahout.cf.taste.example.kddcup.KDDCupDataModel;
import org.apache.mahout.cf.taste.model.DataModel;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
public final class Track1RecommenderEvaluatorRunner {
private static final Logger log = LoggerFactory.getLogger(Track1RecommenderEvaluatorRunner.class);
private Track1RecommenderEvaluatorRunner() {
}
public static void main(String... args) throws IOException, TasteException, OptionException {
File dataFileDirectory = TasteOptionParser.getRatings(args);
if (dataFileDirectory == null) {
throw new IllegalArgumentException("No data directory");
}
if (!dataFileDirectory.exists() || !dataFileDirectory.isDirectory()) {
throw new IllegalArgumentException("Bad data file directory: " + dataFileDirectory);
}
Track1RecommenderEvaluator evaluator = new Track1RecommenderEvaluator(dataFileDirectory);
DataModel model = new KDDCupDataModel(KDDCupDataModel.getTrainingFile(dataFileDirectory));
double evaluation = evaluator.evaluate(new Track1RecommenderBuilder(),
null,
model,
Float.NaN,
Float.NaN);
log.info(String.valueOf(evaluation));
}
}