mahout学习（三）

public class TMahout03 {

    public static void main(String[] args) throws IOException, TasteException {

        //-准确率和召回率评估的配置与运行-//       
        RandomUtils.useTestSeed();
        DataModel model = new FileDataModel(new File("path/ua.base"));

        RecommenderIRStatsEvaluator irStatsEvaluator  = new GenericRecommenderIRStatsEvaluator();
        RecommenderBuilder recommenderBuilder = new RecommenderBuilder() {
            @Override
            public Recommender buildRecommender(DataModel model)
                    throws TasteException {
                UserSimilarity similarity = new PearsonCorrelationSimilarity(model);
                UserNeighborhood neighborhood =
                        new NearestNUserNeighborhood(2, similarity, model);
                return
                        new GenericUserBasedRecommender(model, neighborhood, similarity);
            }
        };
        IRStatistics stats = irStatsEvaluator.evaluate(recommenderBuilder, null, model, null, 2,
                GenericRecommenderIRStatsEvaluator.CHOOSE_THRESHOLD,1.0);
        System.out.println(stats.getPrecision());
        System.out.println(stats.getRecall());

    }

}

//SlopeOneRecommender  @Deprecated。

1 February 2014 - Apache Mahout 0.9 released
 
Apache Mahout has reached version 0.9. All developers are encouraged to begin using version 0.9. Highlights include:
 
    New and improved Mahout website based on Apache CMS - MAHOUT-1245
    Early implementation of a Multi Layer Perceptron (MLP) classifier - MAHOUT-1265
    Scala DSL Bindings for Mahout Math Linear Algebra. See this blogpost and MAHOUT-1297
    Recommenders as Search. See [https://github.com/pferrel/solr-recommender] and MAHOUT-1288
    Support for easy functional Matrix views and derivatives - MAHOUT-1300
    JSON output format for ClusterDumper - MAHOUT-1343
    Enabled randomised testing for all Mahout modules using Carrot RandomizedRunner - MAHOUT-1345
    Online Algorithm for computing accurate Quantiles using 1-dimensional Clustering - See this pdf and MAHOUT-1361
    Upgrade to Lucene 4.6.1 - MAHOUT-1364
 
Changes in 0.9 are detailed in the release notes.
 
The following algorithms that were marked deprecated in 0.8 have been removed in 0.9:
 
    Switched LDA implementation from Gibbs Sampling to Collapsed Variational Bayes
    Meanshift - removed due to lack of actual usage and support
    MinHash - removed due to lack of actual usage and support
    Winnow - removed due to lack of actual usage and support
    Perceptron - removed due to lack of actual usage and support
<span style="color: #ff6600;"><strong>    Slope One - removed due to lack of actual usage</strong></span>
    Distributed Pseudo recommender - removed due to lack of actual usage
    TreeClusteringRecommender - removed due to lack of actual usage