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好吧，我是Mahout和java的新手。我试着评估一个推荐器，下面的代码返回0.0 EVERY TIME，无论我使用的是距离度量还是簇大小。显然，它根本不会分裂培训和测试数据，我不知道为什么。Mahout - Recommender Evaluator返回0.0
对此代码的任何帮助表示赞赏！
public class Example {
public static void main(String[] args) throws Exception {
final DataModel model = new FileDataModel(new File("FILENAME")) ;
RecommenderEvaluator evaluator = new AverageAbsoluteDifferenceRecommenderEvaluator();
RecommenderBuilder recommenderBuilder = new RecommenderBuilder() {
@Override
public Recommender buildRecommender(DataModel dataModel) throws TasteException {
UserSimilarity similarity = new PearsonCorrelationSimilarity(model);
ClusterSimilarity clusterSimilarity = new NearestNeighborClusterSimilarity(similarity);
TreeClusteringRecommender tree = new TreeClusteringRecommender(model, clusterSimilarity, 50);
return tree;
}
} ;
double score = evaluator.evaluate(recommenderBuilder, null, model, .7, 1.0);
System.out.println(score);
}
}
谢谢！