mahout利用布尔型数据评估查准率和查全率

/*利用无偏好值得布尔型
 * 数据评估查准率和查全率
 * */
package byuser;

import java.io.File;
import java.io.IOException;

import org.apache.mahout.cf.taste.common.TasteException;
import org.apache.mahout.cf.taste.eval.DataModelBuilder;
import org.apache.mahout.cf.taste.eval.IRStatistics;
import org.apache.mahout.cf.taste.eval.RecommenderBuilder;
import org.apache.mahout.cf.taste.eval.RecommenderIRStatsEvaluator;
import org.apache.mahout.cf.taste.impl.common.FastByIDMap;
import org.apache.mahout.cf.taste.impl.eval.GenericRecommenderIRStatsEvaluator;
import org.apache.mahout.cf.taste.impl.model.GenericBooleanPrefDataModel;
import org.apache.mahout.cf.taste.impl.model.file.FileDataModel;
import org.apache.mahout.cf.taste.impl.neighborhood.NearestNUserNeighborhood;
import org.apache.mahout.cf.taste.impl.recommender.GenericUserBasedRecommender;
import org.apache.mahout.cf.taste.impl.similarity.LogLikelihoodSimilarity;
import org.apache.mahout.cf.taste.model.DataModel;
import org.apache.mahout.cf.taste.model.PreferenceArray;
import org.apache.mahout.cf.taste.neighborhood.UserNeighborhood;
import org.apache.mahout.cf.taste.recommender.Recommender;
import org.apache.mahout.cf.taste.similarity.UserSimilarity;

public class GenericBooleanPreTest {

	public GenericBooleanPreTest() throws TasteException, IOException{
		DataModel model = new GenericBooleanPrefDataModel(new FileDataModel(new File("E:\\mahout项目\\examples\\ua.base")));
		RecommenderIRStatsEvaluator evaluator = new GenericRecommenderIRStatsEvaluator();
		RecommenderBuilder recommenderBuilder= new RecommenderBuilder() {
			
			@Override
			public Recommender buildRecommender(DataModel model) throws TasteException {
				// TODO Auto-generated method stub
				UserSimilarity similarity = new LogLikelihoodSimilarity(model);
				UserNeighborhood neighborhood = new NearestNUserNeighborhood(10, similarity, model);
				return new GenericUserBasedRecommender(model, neighborhood, similarity);
			}
		};
		
		DataModelBuilder modelBuilder = new DataModelBuilder() {
			
			@Override
			public DataModel buildDataModel(FastByIDMap<PreferenceArray> trainingData) {
				// TODO Auto-generated method stub
				return new GenericBooleanPrefDataModel(GenericBooleanPrefDataModel.toDataMap(trainingData));
			}
		};
		
		IRStatistics stats = evaluator.evaluate(recommenderBuilder, modelBuilder, model, null, 10, GenericRecommenderIRStatsEvaluator.CHOOSE_THRESHOLD, 1.0);
		System.out.println("布尔型数据评估的查准率是：" + stats.getPrecision());
		System.out.println("布尔型数据评估的查全率是：" + stats.getRecall());
		
		
	}
	public static void main(String[] args) throws TasteException, IOException {
		// TODO Auto-generated method stub
		GenericBooleanPreTest test = new GenericBooleanPreTest();

	}

}

结果如图：

mahout利用布尔型数据评估查准率和查全率

原文：http://blog.csdn.net/u012965373/article/details/45536871