在http://libimseti.cz中下載約會的數據集
裏面的ratings.dat有257MB，以逗號分隔，包含用戶ID,檔案ID和評分（檔案ID和用戶ID不是採用同一個匿名方法）
這個數據集經過了預處理，剔除了生成評分個數不到20個的用戶，也剔除了對每個檔案都給出相同分值的用戶
根據《mahout 實戰》中所說，最優的配置是基於用戶的推薦，採用歐氏距離，近鄰數量爲2.
由此寫出的評估程序如下：
public static void evaluateDateData() throws IOException, TasteException
{
DataModel model = new FileDataModel(new File("F:\\mahout\\libimseti\\libimseti-complete\\libimseti\\ratings.dat"));
RecommenderEvaluator evaluator = new AverageAbsoluteDifferenceRecommenderEvaluator();
RecommenderBuilder builder = new RecommenderBuilder(){
@Override
public Recommender buildRecommender(DataModel model)
throws TasteException {
// TODO Auto-generated method stub
UserSimilarity similarity = new EuclideanDistanceSimilarity(model);
UserNeighborhood neighborhood = new NearestNUserNeighborhood(2, similarity, model);
return new GenericUserBasedRecommender(model, neighborhood, similarity);
}
};
double score = evaluator.evaluate(builder, null, model, 0.95, 0.05);
System.out.println(score);
}
運行結果爲0.8415841584158418
在這裏的參數設爲-Xmx1024m