Package com.rapidminer.data

Examples of com.rapidminer.data.SparseBooleanMatrix

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    ///
    public  void SetRatings(IRatings value)
    {
        super.SetRatings(value);
       
        data_item = new SparseBooleanMatrix();
        for (int index = 0; index < super.ratings.Count(); index++)
          data_item.setLocation(ratings.GetItems().get(index), ratings.GetUsers().get(index), true);
    }
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            Attribute at=ar.getAttribute();

            ur=aatr.getRole("user identification");
            i=ur.getAttribute();

            SparseBooleanMatrix mat=new SparseBooleanMatrix();
         
           
              for (Example example : attribute_set) {
             
              double j;

              j=example.getValue(i);
              int iid=user_mapping.ToInternalID((int) j);
             
              j=example.getValue(at);
              int aid=(int)j;
             
              mat.setLocation(iid, aid, true);
            }
            
             UserAttributeKnn recommendAlg=new UserAttributeKnn();
           
            
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          AttributeRole ar=aatr.getRole("attribute identification");
          Attribute at=ar.getAttribute();
          ir=aatr.getRole("item identification");
          i=ir.getAttribute();
         
          SparseBooleanMatrix mat=new SparseBooleanMatrix();
       
         
            for (Example example : attribute_set) {
           
            double j;

            j=example.getValue(i);
            int iid=item_mapping.ToInternalID((int) j);
           
            j=example.getValue(at);
            int aid=(int)j;
            mat.setLocation(iid, aid, true);
          }
         
            System.out.println();
           System.out.println(training_data.GetMaxItemID()+" "+training_data.GetMaxUserID());
          
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    ///
    public void SetRatings(IRatings value)
    {

        super.SetRatings(value);
        data_user = new SparseBooleanMatrix();
        for (int index = 0; index < GetRatings().Count(); index++){
          data_user.setLocation(ratings.GetUsers().get(index), ratings.GetItems().get(index), true);
        }
     
    }
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          Attribute at=ar.getAttribute();
          ir=aatr.getRole("item identification");

          i=ir.getAttribute();
          SparseBooleanMatrix mat=new SparseBooleanMatrix();
         
         
          for (Example example : attribute_set) {
         
          double j;

          j=example.getValue(i);
          int iid=item_mapping.ToInternalID((int) j);
         
          j=example.getValue(at);
          int aid=attribute_mapping.ToInternalID((int)j);
       
          mat.setLocation(iid, aid, true);
        }
       
          
           ItemAttributeKnn recommendAlg=new ItemAttributeKnn();
         
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            AttributeRole ar=aatr.getRole("attribute identification");
            Attribute at=ar.getAttribute();
            ur=aatr.getRole("user identification");
            i=ur.getAttribute();

            SparseBooleanMatrix mat=new SparseBooleanMatrix();
           
           
            for (Example example : attribute_set) {
           
            double j;

            j=example.getValue(i);
            int iid=user_mapping.ToInternalID((int) j);
           
            j=example.getValue(at);
            int aid=(int)j;
           
            mat.setLocation(iid, aid, true);
          }
         
            
             UserAttributeKnn recommendAlg=new UserAttributeKnn();
           
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Related Classes of com.rapidminer.data.SparseBooleanMatrix

  • com.rapidminer.ItemRecommendation.ItemAttributeKnnO
  • com.rapidminer.ItemRecommendation.UserAttributeKnnO
  • com.rapidminer.operator.RatingPrediction._itemKnn
  • com.rapidminer.operator.RatingPrediction._userKnn
  • com.rapidminer.operator.RatingPrediction.ItemAttributeKnnO
  • com.rapidminer.operator.RatingPrediction.UserAttributeKnnO
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