Examples of org.integratedmodelling.riskwiz.learning.data.SparseInstance

Package org.integratedmodelling.riskwiz.learning.data

Examples of org.integratedmodelling.riskwiz.learning.data.SparseInstance

org.integratedmodelling.riskwiz.learning.data.SparseInstance
Class for storing an instance as a sparse vector. A sparse instance only requires storage for those attribute values that are non-zero. Since the objective is to reduce storage requirements for datasets with large numbers of default values, this also includes nominal attributes -- the first nominal value (i.e. that which has index 0) will not require explicit storage, so rearrange your nominal attribute value orderings if necessary. Missing values will be stored explicitly. @author Eibe Frank @version $Revision: 1.20 $

            double[] tempValues = new double[numValues];
            int[] tempIndices = new int[numValues];


            System.arraycopy(m_ValueBuffer, 0, tempValues, 0, numValues);
            System.arraycopy(m_IndicesBuffer, 0, tempIndices, 0, numValues);
            Instance inst = new SparseInstance(1, tempValues, tempIndices,
                    m_Data.numAttributes());


            inst.setDataset(m_Data);
      
            return inst;
        }

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            }
        }
    
        // create instance
        if (sparse) {
            result = new SparseInstance(weight, values);
        } else {
            result = new Instance(weight, values);
        }
    
        return result;

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