Examples of edu.ucla.sspace.clustering.Clustering.cluster()

Class edu.ucla.sspace.clustering.Clustering

Examples of edu.ucla.sspace.clustering.Clustering.cluster()

edu.ucla.sspace.clustering.Clustering.cluster()
Clusters the set of rows in the given {@code Matrix} without a specifiednumber of clusters (optional operation). The set of cluster assignments are returned for each row in the matrix. @param matrix the {@link Matrix} whose row data points are to beclustered @param props the properties to use for any parameters each clusteringalgorithm may need @return an array of {@link Assignment} instances that indicate zero ormore clusters to which each row belongs.

        Properties props = System.getProperties();
        Assignments assignments = null;
        if (sparseVectors.size() > 0) {
            SparseMatrix matrix = Matrices.asSparseMatrix(sparseVectors);
            assignments = (numClusters > 0) 
                ? clustering.cluster(matrix, numClusters, props)
                : clustering.cluster(matrix, props);
        } else {
            Matrix matrix = Matrices.asMatrix(vectors);
            assignments = (numClusters > 0) 
                ? clustering.cluster(matrix, numClusters, props)

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        Assignments assignments = null;
        if (sparseVectors.size() > 0) {
            SparseMatrix matrix = Matrices.asSparseMatrix(sparseVectors);
            assignments = (numClusters > 0) 
                ? clustering.cluster(matrix, numClusters, props)
                : clustering.cluster(matrix, props);
        } else {
            Matrix matrix = Matrices.asMatrix(vectors);
            assignments = (numClusters > 0) 
                ? clustering.cluster(matrix, numClusters, props)
                : clustering.cluster(matrix, props);

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                ? clustering.cluster(matrix, numClusters, props)
                : clustering.cluster(matrix, props);
        } else {
            Matrix matrix = Matrices.asMatrix(vectors);
            assignments = (numClusters > 0) 
                ? clustering.cluster(matrix, numClusters, props)
                : clustering.cluster(matrix, props);
        }


        int a = 0;
        for (String word : words) {

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                : clustering.cluster(matrix, props);
        } else {
            Matrix matrix = Matrices.asMatrix(vectors);
            assignments = (numClusters > 0) 
                ? clustering.cluster(matrix, numClusters, props)
                : clustering.cluster(matrix, props);
        }


        int a = 0;
        for (String word : words) {
            Assignment assignment = assignments.get(a++);

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