Package com.rapidminer.data

Examples of com.rapidminer.data.SparseMatrix_d

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      throw new IllegalArgumentException("entity type must be either USER or ITEM, not " + entity_type);

    ArrayList<ArrayList<Integer>> ratings_by_other_entity = (entity_type == 0) ? ratings.ByItem() : ratings.ByUser();

    SparseMatrix freqs   = new SparseMatrix(num_entities, num_entities);
    SparseMatrix_d i_sums  = new SparseMatrix_d(num_entities, num_entities);
    SparseMatrix_d j_sums  = new SparseMatrix_d(num_entities, num_entities);
    SparseMatrix_d ij_sums = new SparseMatrix_d(num_entities, num_entities);
    SparseMatrix_d ii_sums = new SparseMatrix_d(num_entities, num_entities);
    SparseMatrix_d jj_sums = new SparseMatrix_d(num_entities, num_entities);

    for(int i1=0;i1<ratings_by_other_entity.size();i1++){
      ArrayList<Integer> other_entity_ratings = ratings_by_other_entity.get(i1);
      for (int i = 0; i < other_entity_ratings.size(); i++)
      {
        Integer index1 = other_entity_ratings.get(i);
        int x = (entity_type == 0) ? ratings.GetUsers().get(index1) : ratings.GetItems().get(index1);

        // update pairwise scalar product and frequency
            for (int j = i + 1; j < other_entity_ratings.size(); j++)
        {
          Integer index2 = other_entity_ratings.get(j);
          int y = (entity_type == 0) ? ratings.GetUsers().get(index2) : ratings.GetItems().get(index2);

          double rating1 = ratings.GetValues(index1);
          double rating2 = ratings.GetValues(index2);
         

          // update sums
          if (x < y)
          {
            freqs.setLocation(x, y, freqs.getLocation1(x, y)+1);
            i_sums.setLocation(x, y,i_sums.getLocation1(x, y)+rating1);
            j_sums.setLocation(x, y, j_sums.getLocation1(x, y)+rating2);
            ij_sums.setLocation(x, y,ij_sums.getLocation1(x, y)+rating1*rating2);
            ii_sums.setLocation(x, y, ii_sums.getLocation1(x, y)+rating1*rating1);
            jj_sums.setLocation(x, y, jj_sums.getLocation1(x, y)+rating2*rating2);
          }
          else
          {
            freqs.setLocation(y, x, freqs.getLocation1(y, x)+1);
            i_sums.setLocation(y, x, i_sums.getLocation1(y, x)+rating1);
            j_sums.setLocation(y, x, j_sums.getLocation1(y, x)+rating2);
            ij_sums.setLocation(y, x, ij_sums.getLocation1(y, x)+rating1*rating2);
            ii_sums.setLocation(y, x, ii_sums.getLocation1(y, x)+rating1*rating1);
            jj_sums.setLocation(y, x, jj_sums.getLocation1(y, x)+rating2*rating2);
          }
            }
      }
    }
   
    
     for (int i = 0; i < num_entities; i++)
        this.setLocation(i, i, 1);
   
     List<Tupel<Integer,Integer>> elementi=freqs.NonEmptyEntryIDs();
   
    // fill the entries with interactions
    for (int i1=0;i1<elementi.size();i1++)
    {
     
      Tupel<Integer,Integer> par=elementi.get(i1);
     
      int i=par.getFirst();
      int j=par.getSecond();
      int n = freqs.getLocation(i, j);
     
     
      if (n < 2)
      {
        this.setLocation(i, j, 0);
        continue;
      }

      double numerator = ij_sums.getLocation(i, j) * n - i_sums.getLocation(i, j) * j_sums.getLocation(i, j);

      double denominator = Math.sqrt( (n * ii_sums.getLocation(i, j) - i_sums.getLocation(i, j) * i_sums.getLocation(i, j)) * (n * jj_sums.getLocation(i, j) - j_sums.getLocation(i, j) * j_sums.getLocation(i, j)) );
     
     
      if (denominator == 0)
      {
        this.setLocation(i, j, 0);
View Full Code Here
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      super.RetrainUsers(users);
     
        ArrayList<ArrayList<Integer>> ratings_by_other_entity = ratings.ByUser();

        SparseMatrix freqs   = new SparseMatrix(this.correlation.Getnum_entities(), this.correlation.Getnum_entities());
        SparseMatrix_d i_sums  = new SparseMatrix_d(this.correlation.Getnum_entities(), this.correlation.Getnum_entities());
        SparseMatrix_d j_sums  = new SparseMatrix_d(this.correlation.Getnum_entities(), this.correlation.Getnum_entities());
        SparseMatrix_d ij_sums = new SparseMatrix_d(this.correlation.Getnum_entities(), this.correlation.Getnum_entities());
        SparseMatrix_d ii_sums = new SparseMatrix_d(this.correlation.Getnum_entities(), this.correlation.Getnum_entities());
        SparseMatrix_d jj_sums = new SparseMatrix_d(this.correlation.Getnum_entities(), this.correlation.Getnum_entities());

        for(int i1=0;i1<users.size();i1++){
          ArrayList<Integer> other_entity_ratings = ratings_by_other_entity.get(users.get(i1));
          for (int i = 0; i < other_entity_ratings.size(); i++)
          {
            Integer index1 = other_entity_ratings.get(i);
            int x =  ratings.GetUsers().get(index1);

            // update pairwise scalar product and frequency
               for (int j = i + 1; j < other_entity_ratings.size(); j++)
            {
              Integer index2 = other_entity_ratings.get(j);
              int y = ratings.GetUsers().get(index2);

              double rating1 = ratings.GetValues(index1);
              double rating2 = ratings.GetValues(index2);
             

              // update sums
              if (x < y)
              {
                freqs.setLocation(x, y, freqs.getLocation1(x, y)+1);
                i_sums.setLocation(x, y,i_sums.getLocation1(x, y)+rating1);
                j_sums.setLocation(x, y, j_sums.getLocation1(x, y)+rating2);
                ij_sums.setLocation(x, y,ij_sums.getLocation1(x, y)+rating1*rating2);
                ii_sums.setLocation(x, y, ii_sums.getLocation1(x, y)+rating1*rating1);
                jj_sums.setLocation(x, y, jj_sums.getLocation1(x, y)+rating2*rating2);
              }
              else
              {
                freqs.setLocation(y, x, freqs.getLocation1(y, x)+1);
                i_sums.setLocation(y, x, i_sums.getLocation1(y, x)+rating1);
                j_sums.setLocation(y, x, j_sums.getLocation1(y, x)+rating2);
                ij_sums.setLocation(y, x, ij_sums.getLocation1(y, x)+rating1*rating2);
                ii_sums.setLocation(y, x, ii_sums.getLocation1(y, x)+rating1*rating1);
                jj_sums.setLocation(y, x, jj_sums.getLocation1(y, x)+rating2*rating2);
              }
               }
          }
        }
       
         List<Tupel<Integer,Integer>> elementi=freqs.NonEmptyEntryIDs();
       
        // fill the entries with interactions
        for (int i1=0;i1<elementi.size();i1++)
        {
         
          Tupel<Integer,Integer> par=elementi.get(i1);
         
          int i=par.getFirst();
          int j=par.getSecond();
          int n = freqs.getLocation(i, j);
         
         
          if (n < 2)
          {
            continue;
          }

          double numerator = ij_sums.getLocation(i, j) * n - i_sums.getLocation(i, j) * j_sums.getLocation(i, j);

          double denominator = Math.sqrt( (n * ii_sums.getLocation(i, j) - i_sums.getLocation(i, j) * i_sums.getLocation(i, j)) * (n * jj_sums.getLocation(i, j) - j_sums.getLocation(i, j) * j_sums.getLocation(i, j)) );
         
         
          if (denominator == 0)
          {
            continue;
View Full Code Here
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     super.RetrainItems(items);
    
     ArrayList<ArrayList<Integer>> ratings_by_other_entity = ratings.ByItem();

    SparseMatrix freqs   = new SparseMatrix(this.correlation.Getnum_entities(), this.correlation.Getnum_entities());
    SparseMatrix_d i_sums  = new SparseMatrix_d(this.correlation.Getnum_entities(), this.correlation.Getnum_entities());
    SparseMatrix_d j_sums  = new SparseMatrix_d(this.correlation.Getnum_entities(), this.correlation.Getnum_entities());
    SparseMatrix_d ij_sums = new SparseMatrix_d(this.correlation.Getnum_entities(), this.correlation.Getnum_entities());
    SparseMatrix_d ii_sums = new SparseMatrix_d(this.correlation.Getnum_entities(), this.correlation.Getnum_entities());
    SparseMatrix_d jj_sums = new SparseMatrix_d(this.correlation.Getnum_entities(), this.correlation.Getnum_entities());

    for(int i1=0;i1<items.size();i1++){
      ArrayList<Integer> other_entity_ratings = ratings_by_other_entity.get(items.get(i1));
      for (int i = 0; i < other_entity_ratings.size(); i++)
      {
        Integer index1 = other_entity_ratings.get(i);
        int x =  ratings.GetItems().get(index1);

        // update pairwise scalar product and frequency
           for (int j = i + 1; j < other_entity_ratings.size(); j++)
        {
          Integer index2 = other_entity_ratings.get(j);
          int y = ratings.GetItems().get(index2);

          double rating1 = ratings.GetValues(index1);
          double rating2 = ratings.GetValues(index2);
         

          // update sums
          if (x < y)
          {
            freqs.setLocation(x, y, freqs.getLocation1(x, y)+1);
            i_sums.setLocation(x, y,i_sums.getLocation1(x, y)+rating1);
            j_sums.setLocation(x, y, j_sums.getLocation1(x, y)+rating2);
            ij_sums.setLocation(x, y,ij_sums.getLocation1(x, y)+rating1*rating2);
            ii_sums.setLocation(x, y, ii_sums.getLocation1(x, y)+rating1*rating1);
            jj_sums.setLocation(x, y, jj_sums.getLocation1(x, y)+rating2*rating2);
          }
          else
          {
            freqs.setLocation(y, x, freqs.getLocation1(y, x)+1);
            i_sums.setLocation(y, x, i_sums.getLocation1(y, x)+rating1);
            j_sums.setLocation(y, x, j_sums.getLocation1(y, x)+rating2);
            ij_sums.setLocation(y, x, ij_sums.getLocation1(y, x)+rating1*rating2);
            ii_sums.setLocation(y, x, ii_sums.getLocation1(y, x)+rating1*rating1);
            jj_sums.setLocation(y, x, jj_sums.getLocation1(y, x)+rating2*rating2);
          }
           }
      }
    }
   
     List<Tupel<Integer,Integer>> elementi=freqs.NonEmptyEntryIDs();
   
    // fill the entries with interactions
    for (int i1=0;i1<elementi.size();i1++)
    {
     
      Tupel<Integer,Integer> par=elementi.get(i1);
     
      int i=par.getFirst();
      int j=par.getSecond();
      int n = freqs.getLocation(i, j);
     
     
      if (n < 2)
      {
        continue;
      }

      double numerator = ij_sums.getLocation(i, j) * n - i_sums.getLocation(i, j) * j_sums.getLocation(i, j);

      double denominator = Math.sqrt( (n * ii_sums.getLocation(i, j) - i_sums.getLocation(i, j) * i_sums.getLocation(i, j)) * (n * jj_sums.getLocation(i, j) - j_sums.getLocation(i, j) * j_sums.getLocation(i, j)) );
     
     
      if (denominator == 0)
      {
        continue;
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Related Classes of com.rapidminer.data.SparseMatrix_d

  • com.rapidminer.correlation.Pearson
  • com.rapidminer.operator.RatingPrediction.ItemKnnPearson
  • com.rapidminer.operator.RatingPrediction.UserKnnPearson
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