我在 Mahout 中下载了 Jester 示例代码,并尝试在 jester 数据集上运行它以查看评估结果。运行成功,但控制台只有结果:
log4j:WARN No appenders could be found for logger (org.apache.mahout.cf.taste.impl.model.file.FileDataModel).
log4j:WARN Please initialize the log4j system properly.
log4j:WARN See http://logging.apache.org/log4j/1.2/faq.html#noconfig for more info.
我希望看到评估分数范围从 0 到 10。任何人都可以帮助我找出如何获得分数?
我正在使用 mahout-core-0.6.jar,以下是代码:
JesterDataModel.java:
package Jester;
import java.io.File;
import java.io.IOException;
import java.util.Collection;
import java.util.regex.Pattern;
import com.google.common.collect.Lists;
import org.apache.mahout.cf.taste.example.grouplens.GroupLensDataModel;
import org.apache.mahout.cf.taste.impl.common.FastByIDMap;
import org.apache.mahout.cf.taste.impl.model.GenericDataModel;
import org.apache.mahout.cf.taste.impl.model.GenericPreference;
import org.apache.mahout.cf.taste.impl.model.file.FileDataModel;
import org.apache.mahout.cf.taste.model.DataModel;
import org.apache.mahout.cf.taste.model.Preference;
import org.apache.mahout.common.iterator.FileLineIterator;
//import org.apache.mahout.cf.taste.impl.common.FileLineIterable;
public final class JesterDataModel extends FileDataModel {
private static final Pattern COMMA_PATTERN = Pattern.compile(",");
private long userBeingRead;
public JesterDataModel() throws IOException {
this(GroupLensDataModel.readResourceToTempFile("\\jester-data-1.csv"));
}
public JesterDataModel(File ratingsFile) throws IOException {
super(ratingsFile);
}
@Override
public void reload() {
userBeingRead = 0;
super.reload();
}
@Override
protected DataModel buildModel() throws IOException {
FastByIDMap<Collection<Preference>> data = new FastByIDMap<Collection<Preference>> ();
FileLineIterator iterator = new FileLineIterator(getDataFile(), false);
FastByIDMap<FastByIDMap<Long>> timestamps = new FastByIDMap<FastByIDMap<Long>>();
processFile(iterator, data, timestamps, false);
return new GenericDataModel(GenericDataModel.toDataMap(data, true));
}
@Override
protected void processLine(String line,
FastByIDMap<?> rawData,
FastByIDMap<FastByIDMap<Long>> timestamps,
boolean fromPriorData) {
FastByIDMap<Collection<Preference>> data = (FastByIDMap<Collection<Preference>>) rawData;
String[] jokePrefs = COMMA_PATTERN.split(line);
int count = Integer.parseInt(jokePrefs[0]);
Collection<Preference> prefs = Lists.newArrayListWithCapacity(count);
for (int itemID = 1; itemID < jokePrefs.length; itemID++) { // yes skip first one, just a count
String jokePref = jokePrefs[itemID];
if (!"99".equals(jokePref)) {
float jokePrefValue = Float.parseFloat(jokePref);
prefs.add(new GenericPreference(userBeingRead, itemID, jokePrefValue));
}
}
data.put(userBeingRead, prefs);
userBeingRead++;
}
}
JesterRecommenderEvaluatorRunner.java
package Jester;
import org.apache.mahout.cf.taste.common.TasteException;
import org.apache.mahout.cf.taste.eval.RecommenderEvaluator;
import org.apache.mahout.cf.taste.impl.eval.AverageAbsoluteDifferenceRecommenderEvaluator;
import org.apache.mahout.cf.taste.model.DataModel;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import java.io.IOException;
public final class JesterRecommenderEvaluatorRunner {
private static final Logger log = LoggerFactory.getLogger(JesterRecommenderEvaluatorRunner.class);
private JesterRecommenderEvaluatorRunner() {
// do nothing
}
public static void main(String... args) throws IOException, TasteException {
RecommenderEvaluator evaluator = new AverageAbsoluteDifferenceRecommenderEvaluator();
DataModel model = new JesterDataModel();
double evaluation = evaluator.evaluate(new JesterRecommenderBuilder(),
null,
model,
0.9,
1.0);
log.info(String.valueOf(evaluation));
}
}