Package edu.ucla.sspace.similarity

Examples of edu.ucla.sspace.similarity.CosineSimilarity

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        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);
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    /**
     * Creates this {@code SimpleNearestNeighborFinder} with as many threads as
     * processors, and using the cosine similarity for word comparisons.
     */
    public SimpleNearestNeighborFinder(SemanticSpace sspace) {
        this(sspace, new CosineSimilarity(),
             Runtime.getRuntime().availableProcessors());
    }
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    /**
     * Creates this {@code SimpleNearestNeighborFinder} with the specified
     * number of threads, using the cosine similarity for word comparisons.
     */
    public SimpleNearestNeighborFinder(SemanticSpace sspace, int numThreads) {
        this(sspace, new CosineSimilarity(), numThreads);
    }
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        this.creator = creator;
        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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    public static SimilarityFunction getSimilarityFunction(
            SimType similarityType) {
        switch (similarityType) {
            case COSINE:
                return new CosineSimilarity();
            case PEARSON_CORRELATION:
                return new PearsonCorrelation();
            case EUCLIDEAN:
                return new EuclideanSimilarity();
            case SPEARMAN_RANK_CORRELATION:
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        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);
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     * Creates a {@link NeighborChainAgglomerativeClustering} with no minimum
     * similarity threshold.  When using this constructor, you must specifcy the
     * number of clusters or the results will be undefined.
     */
    public NeighborChainAgglomerativeClustering() {
        this(ClusterLink.MEAN_LINK, new CosineSimilarity());
    }
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Related Classes of edu.ucla.sspace.similarity.CosineSimilarity

  • edu.ucla.sspace.clustering.DataMatrixLinkClustering
  • edu.ucla.sspace.clustering.NeighborChainAgglomerativeClustering
  • edu.ucla.sspace.common.Similarity
  • edu.ucla.sspace.mains.LpcsMain
  • edu.ucla.sspace.mains.LpsaMain
  • edu.ucla.sspace.util.SimpleNearestNeighborFinder
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