Package edu.ucla.sspace.basis

Examples of edu.ucla.sspace.basis.StringBasisMapping


    /**
     * Constructs a new {@link PreComputedContextExtractor} using a {@link
     * StringBasisMapping}.
     */
    public PreComputedContextExtractor() {
        this(new StringBasisMapping());
    }
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    /**
     * Constructs a new instance using the default parameters used in the
     * original publication.
     */
    public HyperspaceAnalogueToLanguage() {
        this(new StringBasisMapping(),
             DEFAULT_WINDOW_SIZE,
             new LinearWeighting(),
             -1d,
             -1);
    }
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                transform = ReflectionUtil.getObjectInstance(
                        argOptions.getStringOption("preprocess"));
            String algName = argOptions.getStringOption("svdAlgorithm", "ANY");
            SingularValueDecomposition factorization = SVD.getFactorization(
                    Algorithm.valueOf(algName.toUpperCase()));
            basis = new StringBasisMapping();

            return new LatentSemanticAnalysis(
                false, dimensions, transform, factorization, false, basis);
        } catch (IOException ioe) {
            throw new IOError(ioe);
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     */
    public StructuredVectorSpace(DependencyExtractor extractor,
                                 DependencyPathAcceptor acceptor,
                                 VectorCombinor combinor) {
        this(extractor, acceptor, combinor,
             new StringBasisMapping(), new HashSet<String>());
    }
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        int windowSize = argOptions.getIntOption('s', 5);
        double threshold = argOptions.getDoubleOption('h', -1d);
        int retain = argOptions.getIntOption('r', -1);

        return new HyperspaceAnalogueToLanguage(
                new StringBasisMapping(), windowSize, weighting,
                threshold, retain);
    }
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                transform = ReflectionUtil.getObjectInstance(
                        argOptions.getStringOption("preprocess"));
            String algName = argOptions.getStringOption("svdAlgorithm", "ANY");
            MatrixFactorization factorization =
                new NonNegativeMatrixFactorizationMultiplicative();
            basis = new StringBasisMapping();

            throw new IOException("Not sure what to do");
//             return new LatentSemanticAnalysis(
//                 true, dimensions, transform, factorization, false, basis);
        } catch (IOException ioe) {
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     * document space is <i>not</i> retained.
     */
    public LatentSemanticAnalysis() throws IOException {
        this(false, 300, new LogEntropyTransform(),
             SVD.getFastestAvailableFactorization(),
             false, new StringBasisMapping());
    }
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     * @param dimensions The number of dimensions to retain in the reduced space
     */
    public LatentSemanticAnalysis(int numDimensions) throws IOException {
        this(false, numDimensions, new LogEntropyTransform(),
             SVD.getFastestAvailableFactorization(),
             false, new StringBasisMapping());
    }
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    public LatentSemanticAnalysis(int numDimensions,
                                  SingularValueDecomposition svdMethod)
            throws IOException {
        this(false, numDimensions, new LogEntropyTransform(),
             svdMethod,
             false, new StringBasisMapping());
    }
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    public LatentSemanticAnalysis(int numDimensions,
                                  boolean retainDocumentSpace)
            throws IOException {
        this(retainDocumentSpace, numDimensions, new LogEntropyTransform(),
             SVD.getFastestAvailableFactorization(),
             false, new StringBasisMapping());
    }
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