@Test public void testExtractUnsupervisedLabeled() { final DataSet ds1 = generateTestData(); final List<BasicData> result = ds1.extractUnsupervisedLabeled(0); assertEquals(3, result.size()); assertTrue(result.get(0).getLabel().equals("One")); }
public List<BasicData> extractUnsupervisedLabeled(final int labelIndex) { final List<BasicData> result = new ArrayList<BasicData>(); final int dimensions = getHeaderCount() - 1; for (int rowIndex = 0; rowIndex < size(); rowIndex++) { final Object[] raw = this.data.get(rowIndex); final BasicData row = new BasicData(dimensions, 0, raw[labelIndex].toString()); int colIndex = 0; for (int rawColIndex = 0; rawColIndex < getHeaderCount(); rawColIndex++) { if (rawColIndex != labelIndex) { row.getInput()[colIndex++] = convertNumeric(raw, rawColIndex); } } result.add(row); } return result; }
DataSet { public List<BasicData> extractUnsupervisedLabeled(final int labelIndex) { final List<BasicData> result = new ArrayList<BasicData>(); final int dimensions = getHeaderCount() - 1; for (int rowIndex = 0; rowIndex < size(); rowIndex++) { final Object[] raw = this.data.get(rowIndex); final BasicData row = new BasicData(dimensions, 0, raw[labelIndex].toString()); int colIndex = 0; for (int rawColIndex = 0; rawColIndex < getHeaderCount(); rawColIndex++) { if (rawColIndex != labelIndex) { row.getInput()[colIndex++] = convertNumeric(raw, rawColIndex); } } result.add(row); } return result; } }
DataSet { public List<BasicData> extractUnsupervisedLabeled(final int labelIndex) { final List<BasicData> result = new ArrayList<BasicData>(); final int dimensions = getHeaderCount() - 1; for (int rowIndex = 0; rowIndex < size(); rowIndex++) { final Object[] raw = this.data.get(rowIndex); final BasicData row = new BasicData(dimensions, 0, raw[labelIndex].toString()); int colIndex = 0; for (int rawColIndex = 0; rawColIndex < getHeaderCount(); rawColIndex++) { if (rawColIndex != labelIndex) { row.getInput()[colIndex++] = convertNumeric(raw, rawColIndex); } } result.add(row); } return result; } DataSet(final String[] theHeaders); }
DataSet { public List<BasicData> extractUnsupervisedLabeled(final int labelIndex) { final List<BasicData> result = new ArrayList<BasicData>(); final int dimensions = getHeaderCount() - 1; for (int rowIndex = 0; rowIndex < size(); rowIndex++) { final Object[] raw = this.data.get(rowIndex); final BasicData row = new BasicData(dimensions, 0, raw[labelIndex].toString()); int colIndex = 0; for (int rawColIndex = 0; rawColIndex < getHeaderCount(); rawColIndex++) { if (rawColIndex != labelIndex) { row.getInput()[colIndex++] = convertNumeric(raw, rawColIndex); } } result.add(row); } return result; } DataSet(final String[] theHeaders); static DataSet load(final File filename); static DataSet load(final InputStream is); static void save(final File filename, final DataSet ds); static void save(final OutputStream os, final DataSet ds); int getHeaderCount(); String[] getHeaders(); void add(final Object[] row); List<Object[]> getData(); double getMax(final int column); double getMin(final int column); void normalizeRange(final int column, final double dataLow, final double dataHigh, final double normalizedLow, final double normalizedHigh); void normalizeRange(final int column, final double normalizedLow, final double normalizedHigh); void deNormalizeRange(final int column, final double dataLow, final double dataHigh, final double normalizedLow, final double normalizedHigh); void normalizeReciprocal(final int column); void deNormalizeReciprocal(final int column); Map<String, Integer> enumerateClasses(final int column); Map<String, Integer> encodeNumeric(final int column); Map<String, Integer> encodeOneOfN(final int column); Map<String, Integer> encodeOneOfN(final int column, final double offValue, final double onValue); Map<String, Integer> encodeEquilateral(final int column); Map<String, Integer> encodeEquilateral(final int column, final double offValue, final double onValue); int size(); void appendColumns(final int count); void insertColumns(final int column, final int columnCount); @Override boolean equals(final Object other); List<BasicData> extractUnsupervisedLabeled(final int labelIndex); List<BasicData> extractSupervised(final int inputBegin, final int inputCount, final int idealBegin, final int idealCount); void deleteUnknowns(); void deleteColumn(final int col); void replaceColumn(final int columnIndex, final double searchFor, final double replaceWith, final double others); }
DataSet { public List<BasicData> extractUnsupervisedLabeled(final int labelIndex) { final List<BasicData> result = new ArrayList<BasicData>(); final int dimensions = getHeaderCount() - 1; for (int rowIndex = 0; rowIndex < size(); rowIndex++) { final Object[] raw = this.data.get(rowIndex); final BasicData row = new BasicData(dimensions, 0, raw[labelIndex].toString()); int colIndex = 0; for (int rawColIndex = 0; rawColIndex < getHeaderCount(); rawColIndex++) { if (rawColIndex != labelIndex) { row.getInput()[colIndex++] = convertNumeric(raw, rawColIndex); } } result.add(row); } return result; } DataSet(final String[] theHeaders); static DataSet load(final File filename); static DataSet load(final InputStream is); static void save(final File filename, final DataSet ds); static void save(final OutputStream os, final DataSet ds); int getHeaderCount(); String[] getHeaders(); void add(final Object[] row); List<Object[]> getData(); double getMax(final int column); double getMin(final int column); void normalizeRange(final int column, final double dataLow, final double dataHigh, final double normalizedLow, final double normalizedHigh); void normalizeRange(final int column, final double normalizedLow, final double normalizedHigh); void deNormalizeRange(final int column, final double dataLow, final double dataHigh, final double normalizedLow, final double normalizedHigh); void normalizeReciprocal(final int column); void deNormalizeReciprocal(final int column); Map<String, Integer> enumerateClasses(final int column); Map<String, Integer> encodeNumeric(final int column); Map<String, Integer> encodeOneOfN(final int column); Map<String, Integer> encodeOneOfN(final int column, final double offValue, final double onValue); Map<String, Integer> encodeEquilateral(final int column); Map<String, Integer> encodeEquilateral(final int column, final double offValue, final double onValue); int size(); void appendColumns(final int count); void insertColumns(final int column, final int columnCount); @Override boolean equals(final Object other); List<BasicData> extractUnsupervisedLabeled(final int labelIndex); List<BasicData> extractSupervised(final int inputBegin, final int inputCount, final int idealBegin, final int idealCount); void deleteUnknowns(); void deleteColumn(final int col); void replaceColumn(final int columnIndex, final double searchFor, final double replaceWith, final double others);  }