Examples with AutoBinnerLearnSettings org.knime.base.node.preproc.autobinner3.AutoBinnerLearnSettings used on opensource projects

Example 1 with AutoBinnerLearnSettings

use of org.knime.base.node.preproc.autobinner3.AutoBinnerLearnSettings in project knime-core by knime.

the class DBAutoBinner method createPMMLPrepocDiscretize.

/**
 * This method creates a {@link PMMLPreprocDiscretize} object and is used in {@link DBAutoBinnerNodeModel}
 *
 * @param cp {@link CredentialsProvider}
 * @param connectionSettings {@link DatabaseQueryConnectionSettings}
 * @param dataTableSpec DataTableSpec of incoming {@link BufferedDataTable}
 * @return a {@link PMMLPreprocDiscretize} object containing required parameters for binning operation
 * @throws SQLException
 */
public PMMLPreprocDiscretize createPMMLPrepocDiscretize(final CredentialsProvider cp, final DatabaseQueryConnectionSettings connectionSettings, final DataTableSpec dataTableSpec) throws SQLException {
    final String query = connectionSettings.getQuery();
    final StatementManipulator statementManipulator = connectionSettings.getUtility().getStatementManipulator();
    AutoBinnerLearnSettings settings = getSettings();
    String[] includeCols = settings.getFilterConfiguration().applyTo(dataTableSpec).getIncludes();
    if (includeCols.length == 0) {
        return createDisretizeOp(new LinkedHashMap<>());
    }
    StringBuilder minMaxQuery = new StringBuilder();
    minMaxQuery.append("SELECT");
    for (int i = 0; i < includeCols.length; i++) {
        minMaxQuery.append(" MAX(" + statementManipulator.quoteIdentifier(includeCols[i]) + ") " + statementManipulator.quoteIdentifier("max_" + includeCols[i]) + ",");
        minMaxQuery.append(" MIN(" + statementManipulator.quoteIdentifier(includeCols[i]) + ") " + statementManipulator.quoteIdentifier("min_" + includeCols[i]));
        if (i < includeCols.length - 1) {
            minMaxQuery.append(",");
        }
    }
    minMaxQuery.append(" FROM (" + query + ") T");
    HashMap<String, Pair<Double, Double>> maxAndMin = connectionSettings.execute(cp, conn -> {
        double max = 0;
        double min = 0;
        HashMap<String, Pair<Double, Double>> maxMinMap = new LinkedHashMap<>();
        try (ResultSet valueSet = conn.createStatement().executeQuery(minMaxQuery.toString())) {
            while (valueSet.next()) {
                for (int i = 0; i < includeCols.length; i++) {
                    max = valueSet.getDouble("max_" + includeCols[i]);
                    min = valueSet.getDouble("min_" + includeCols[i]);
                    maxMinMap.put(includeCols[i], new Pair<Double, Double>(min, max));
                }
            }
        }
        return maxMinMap;
    });
    int number = settings.getBinCount();
    Map<String, double[]> edgesMap = new LinkedHashMap<>();
    for (Entry<String, Pair<Double, Double>> entry : maxAndMin.entrySet()) {
        double[] edges = AutoBinner.calculateBounds(number, entry.getValue().getFirst(), entry.getValue().getSecond());
        if (settings.getIntegerBounds()) {
            edges = AutoBinner.toIntegerBoundaries(edges);
        }
        edgesMap.put(entry.getKey(), edges);
    }
    return createDisretizeOp(edgesMap);
}

Example 2 with AutoBinnerLearnSettings

use of org.knime.base.node.preproc.autobinner3.AutoBinnerLearnSettings in project knime-core by knime.

the class DBAutoBinnerNodeModel method validateSettings.

/**
 * {@inheritDoc}
 */
@Override
protected void validateSettings(final NodeSettingsRO settings) throws InvalidSettingsException {
    AutoBinnerLearnSettings s = new AutoBinnerLearnSettings();
    s.loadSettings(settings);
}