Examples of AffinityMatrixCreator

edu.ucla.sspace.matrix.AffinityMatrixCreator
A functional class that given a matrix or matrix file, computes the affinity matrix for the rows in that matrix. For an {@code n} x {@code m} matrix, theaffinity matrix is an {@code n} x {@code n} matrix specifying which of therows are connected; viewed as a graph, the affinity matrix specifies which rows have edges between them and what the weights of those edges are.
This class provides multiple options for specifying how the affinity matrix should be computed both in terms of the number of neighbors and the weights of the edges to those neighbors.
Due to the full density of the affinity matrix, the matrix is always written to disk, rather than stored in memory. This class also provides support for computing the affinity matrix off-core, i.e. without needing to load the matrix entirely into memory. If the off-core method is specified, the returned matrix will also be on disk.
This class is thread safe. @see LocalityPreservingProjection

Examples of edu.ucla.sspace.matrix.AffinityMatrixCreator

            t.printStackTrace();
        }
    }
    
    protected SemanticSpace getSpace() {
        AffinityMatrixCreator creator = ReflectionUtil.getObjectInstance(
                argOptions.getStringOption('e'));
        if (argOptions.hasOption("edgeTypeParam"))
            creator.setParams(argOptions.getIntOption("edgeTypeParam"));


        SimilarityFunction edgeSim = new CosineSimilarity();
        SimilarityFunction kernelSim = ReflectionUtil.getObjectInstance(
                argOptions.getStringOption("edgeWeighting"));
        if (argOptions.hasOption("edgeWeighting"))
            kernelSim.setParams(argOptions.getIntOption("edgeWeightingParam"));
        creator.setFunctions(edgeSim, kernelSim);


        return new LocalityPreservingCooccurrenceSpace(creator);
    }

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Examples of edu.ucla.sspace.matrix.AffinityMatrixCreator

        this.linkCluster = new LinkClustering(); 
    }


    public static AffinityMatrixCreator createDefaultAffinityMatrixCreator() {
        SimilarityFunction simFunc = new CosineSimilarity();
        AffinityMatrixCreator creator =
            new NearestNeighborAffinityMatrixCreator();
        creator.setParams(10);
        creator.setFunctions(simFunc, simFunc);
        return creator;
    }

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Examples of edu.ucla.sspace.matrix.AffinityMatrixCreator

            t.printStackTrace();
        }
    }
    
    protected SemanticSpace getSpace() {
        AffinityMatrixCreator creator = ReflectionUtil.getObjectInstance(
                argOptions.getStringOption('e'));
        if (argOptions.hasOption("edgeTypeParam"))
            creator.setParams(argOptions.getIntOption("edgeTypeParam"));


        SimilarityFunction edgeSim = new CosineSimilarity();
        SimilarityFunction kernelSim = ReflectionUtil.getObjectInstance(
                argOptions.getStringOption("edgeWeighting"));
        if (argOptions.hasOption("edgeWeighting"))
            kernelSim.setParams(argOptions.getIntOption("edgeWeightingParam"));
        creator.setFunctions(edgeSim, kernelSim);


        try {
            return new LocalityPreservingSemanticAnalysis(creator);
        } catch (IOException ioe) {
            throw new IOError(ioe);

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