Examples of KnnItemBasedRecommender

org.apache.mahout.cf.taste.impl.recommender.knn.KnnItemBasedRecommender

The weights to compute the final predicted preferences are calculated using linear interpolation, through an {@link Optimizer}. This algorithm is based in the paper of Robert M. Bell and Yehuda Koren in ICDM '07.

Examples of org.apache.mahout.cf.taste.impl.recommender.knn.KnnItemBasedRecommender

class KnnBasedRecommender {


  Recommender buildRecommender(DataModel model) {
    ItemSimilarity similarity = new LogLikelihoodSimilarity(model);
    Optimizer optimizer = new ConjugateGradientOptimizer();
    return new KnnItemBasedRecommender(model, similarity, optimizer, 10);
  }

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