Package org.apache.mahout.cf.taste.impl.similarity

Examples of org.apache.mahout.cf.taste.impl.similarity.PearsonCorrelationSimilarity.userSimilarity()

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      PearsonCorrelationSimilarity pearsonSimilarity = new PearsonCorrelationSimilarity(model);
     
      // Java: Similarity between Wolf and Bear: 0.8196561646738477
      // R: corr(c(8,3,1),c(8,7,2)): 0.8196562
      System.out.println("Similarity between Wolf and Bear: "+pearsonSimilarity.userSimilarity(id2thing.toLongID("Wolf"), id2thing.toLongID("Bear")));
      // Similarity between Wolf and Rabbit: -0.6465846072812313
      // R: cor(c(8,3,1),c(2,1,10)): -0.6465846
      System.out.println("Similarity between Wolf and Rabbit: "+pearsonSimilarity.userSimilarity(id2thing.toLongID("Wolf"), id2thing.toLongID("Rabbit")));
      // Similarity between Wolf and Pinguin: -0.24019223070763077
      // R: cor(c(8,3,1),c(2,10,2)): -0.2401922
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      // Java: Similarity between Wolf and Bear: 0.8196561646738477
      // R: corr(c(8,3,1),c(8,7,2)): 0.8196562
      System.out.println("Similarity between Wolf and Bear: "+pearsonSimilarity.userSimilarity(id2thing.toLongID("Wolf"), id2thing.toLongID("Bear")));
      // Similarity between Wolf and Rabbit: -0.6465846072812313
      // R: cor(c(8,3,1),c(2,1,10)): -0.6465846
      System.out.println("Similarity between Wolf and Rabbit: "+pearsonSimilarity.userSimilarity(id2thing.toLongID("Wolf"), id2thing.toLongID("Rabbit")));
      // Similarity between Wolf and Pinguin: -0.24019223070763077
      // R: cor(c(8,3,1),c(2,10,2)): -0.2401922
      System.out.println("Similarity between Wolf and Pinguin: "+pearsonSimilarity.userSimilarity(id2thing.toLongID("Wolf"), id2thing.toLongID("Pinguin")));
     
      GenericUserBasedRecommender recommender = new GenericUserBasedRecommender(model, new NearestNUserNeighborhood(3, pearsonSimilarity, model), pearsonSimilarity);
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      // Similarity between Wolf and Rabbit: -0.6465846072812313
      // R: cor(c(8,3,1),c(2,1,10)): -0.6465846
      System.out.println("Similarity between Wolf and Rabbit: "+pearsonSimilarity.userSimilarity(id2thing.toLongID("Wolf"), id2thing.toLongID("Rabbit")));
      // Similarity between Wolf and Pinguin: -0.24019223070763077
      // R: cor(c(8,3,1),c(2,10,2)): -0.2401922
      System.out.println("Similarity between Wolf and Pinguin: "+pearsonSimilarity.userSimilarity(id2thing.toLongID("Wolf"), id2thing.toLongID("Pinguin")));
     
      GenericUserBasedRecommender recommender = new GenericUserBasedRecommender(model, new NearestNUserNeighborhood(3, pearsonSimilarity, model), pearsonSimilarity);
      for(RecommendedItem r : recommender.recommend(id2thing.toLongID("Wolf"), 3)) {
        // Pork:
        // (0.8196561646738477 * 8 + (-0.6465846072812313) * 1) / (0.8196561646738477 + (-0.6465846072812313)) = 34,15157 ~ 10
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