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mahout推荐3-评估查准率和查全率

2024-07-15 15:26:39   214人阅读

通过估计偏好值来生成推荐结果并非绝对必要。给出一个从优到劣的推荐列表对于许多场景都够用了，而不必包含估计的偏好值。

查准率：在top结果中相关结果的比例

查全率：所有相关结果，包含在top结果中的比例

对上个例子进行测试：

package mahout;import java.io.File;import org.apache.mahout.cf.taste.common.TasteException;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.eval.GenericRecommenderIRStatsEvaluator;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.PearsonCorrelationSimilarity;import org.apache.mahout.cf.taste.model.DataModel;import org.apache.mahout.cf.taste.neighborhood.UserNeighborhood;import org.apache.mahout.cf.taste.recommender.Recommender;import org.apache.mahout.cf.taste.similarity.UserSimilarity;import org.apache.mahout.common.RandomUtils;public class IRStatsEvalutator {	public static void main(String[] args) throws Exception {		RandomUtils.useTestSeed();		DataModel dataModel = new FileDataModel(new File("data/intro.csv"));		RecommenderIRStatsEvaluator evaluator = new GenericRecommenderIRStatsEvaluator();		//用于生成推荐引擎的构建器，与上一例子实现相同		RecommenderBuilder builder = new RecommenderBuilder() {						public Recommender buildRecommender(DataModel model) throws TasteException {				// TODO Auto-generated method stub				//用户相似度，多种方法				UserSimilarity similarity = new PearsonCorrelationSimilarity(model);				//用户邻居				UserNeighborhood neighborhood = new NearestNUserNeighborhood(2, similarity, model);				//一个推荐器				return new GenericUserBasedRecommender(model, neighborhood, similarity);			}		};		//评估推荐2个结果时的查准率和查全率		IRStatistics statistics = evaluator.evaluate(builder, null, dataModel, null, 2, GenericRecommenderIRStatsEvaluator.CHOOSE_THRESHOLD, 1.0);				System.out.println("查准率："+statistics.getPrecision());		System.out.println("查全率："+statistics.getRecall());	}}

 输出结果：

14/08/04 09:46:21 INFO file.FileDataModel: Creating FileDataModel for file data\intro.csv14/08/04 09:46:21 INFO file.FileDataModel: Reading file info...14/08/04 09:46:21 INFO file.FileDataModel: Read lines: 2114/08/04 09:46:21 INFO model.GenericDataModel: Processed 5 users14/08/04 09:46:21 INFO model.GenericDataModel: Processed 5 users14/08/04 09:46:21 INFO model.GenericDataModel: Processed 5 users14/08/04 09:46:21 INFO eval.GenericRecommenderIRStatsEvaluator: Evaluated with user 2 in 31ms14/08/04 09:46:21 INFO eval.GenericRecommenderIRStatsEvaluator: Precision/recall/fall-out/nDCG/reach: 1.0 / 1.0 / 0.0 / 1.0 / 1.014/08/04 09:46:21 INFO model.GenericDataModel: Processed 5 users14/08/04 09:46:21 INFO eval.GenericRecommenderIRStatsEvaluator: Evaluated with user 4 in 0ms14/08/04 09:46:21 INFO eval.GenericRecommenderIRStatsEvaluator: Precision/recall/fall-out/nDCG/reach: 0.75 / 1.0 / 0.08333333333333333 / 1.0 / 1.0查准率：0.75查全率：1.0

 文件描述：见《mahout in Action》


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