/** * {@inheritDoc} */ public void processSpace(Properties props) { filter.transform(bigramMatrix, bigramMatrix); basis.setReadOnly(true); } }
Transform tfidf = new TfIdfDocStripedTransform(); Transform rowMag = new RowMagnitudeTransform(); m = rowMag.transform(tfidf.transform(m)); Matrix[] gapMatrices = new Matrix[numGaps]; for (int i = 0; i < numGaps; ++i) gapMatrices[i] = rowMag.transform(tfidf.transform( generator.generateTestData()));
Matrix transformed = transform.transform(m);
Transform tfidf = new TfIdfDocStripedTransform(); Transform rowMag = new RowMagnitudeTransform(); m = rowMag.transform(tfidf.transform(m)); Matrix[] gapMatrices = new Matrix[numGaps]; for (int i = 0; i < numGaps; ++i) gapMatrices[i] = rowMag.transform(tfidf.transform( generator.generateTestData()));
/** * {@inheritDoc} */ public void processSpace(Properties properties) { SparseMatrix cleanedMatrix = (SparseMatrix) transform.transform( cooccurrenceMatrix); for (String term : basis.keySet()) { int index = basis.getDimension(term); SparseDoubleVector sdv = cleanedMatrix.getRowVector(index); double score = 0; for (int i : sdv.getNonZeroIndices()) score += sdv.get(i); wordScores.put(term, score); } }
finalCorrelation = transform.transform(finalCorrelation); COALS_LOGGER.info("Done normalizing co-occurrance matrix.");
finalCorrelation = transform.transform(finalCorrelation); COALS_LOGGER.info("Done normalizing co-occurrance matrix.");
/** * {@inheritDoc} */ public void processSpace(Properties properties) { SparseMatrix cleanedMatrix = (SparseMatrix) transform.transform( cooccurrenceMatrix); for (String term : basis.keySet()) { int index = basis.getDimension(term); SparseDoubleVector sdv = cleanedMatrix.getRowVector(index); double score = 0; for (int i : sdv.getNonZeroIndices()) score += sdv.get(i); wordScores.put(term, score); } }
/** * {@inheritDoc} */ public void processSpace(Properties properties) { SparseMatrix cleanedMatrix = (SparseMatrix) transform.transform( cooccurrenceMatrix); for (String term : basis.keySet()) { int index = basis.getDimension(term); SparseDoubleVector sdv = cleanedMatrix.getRowVector(index); double score = 0; for (int i : sdv.getNonZeroIndices()) score += sdv.get(i); wordScores.put(term, score); } }
/** * {@inheritDoc} */ public void processSpace(Properties properties) { SparseMatrix cleanedMatrix = (SparseMatrix) transform.transform( cooccurrenceMatrix); for (String term : basis.keySet()) { int index = basis.getDimension(term); SparseDoubleVector sdv = cleanedMatrix.getRowVector(index); double score = 0; for (int i : sdv.getNonZeroIndices()) score += sdv.get(i); wordScores.put(term, score); } }
File transformedMatrix = transform.transform(termDocumentMatrix, termDocumentMatrixBuilder.getMatrixFormat());
File transformedMatrix = transform.transform(termDocumentMatrix, termDocumentMatrixBuilder.getMatrixFormat());
termDocumentMatrix = transform.transform( termDocumentMatrix, termDocumentMatrixBuilder.getMatrixFormat());
termDocumentMatrix = transform.transform( termDocumentMatrix, termDocumentMatrixBuilder.getMatrixFormat());
DoubleVector transformed = transform.transform(docVec);