Examples with TreeNodeCondition org.knime.base.node.mine.treeensemble2.model.TreeNodeCondition used on opensource projects

Example 6 with TreeNodeCondition

use of org.knime.base.node.mine.treeensemble2.model.TreeNodeCondition in project knime-core by knime.

the class TreeBitVectorColumnData method updateChildMemberships.

/**
 * {@inheritDoc}
 */
@Override
public BitSet updateChildMemberships(final TreeNodeCondition childCondition, final DataMemberships parentMemberships) {
    TreeNodeBitCondition bitCondition = (TreeNodeBitCondition) childCondition;
    assert getMetaData().getAttributeName().equals(bitCondition.getColumnMetaData().getAttributeName());
    final boolean value = bitCondition.getValue();
    final ColumnMemberships columnMemberships = parentMemberships.getColumnMemberships(getMetaData().getAttributeIndex());
    BitSet inChild = new BitSet(columnMemberships.size());
    columnMemberships.reset();
    columnMemberships.next();
    for (int i = columnMemberships.getIndexInColumn(); ; i = columnMemberships.getIndexInColumn()) {
        if (m_columnBitSet.get(i) == value) {
            inChild.set(columnMemberships.getIndexInDataMemberships());
        }
        if (!columnMemberships.next()) {
            break;
        }
    }
    return inChild;
}

Example 7 with TreeNodeCondition

use of org.knime.base.node.mine.treeensemble2.model.TreeNodeCondition in project knime-core by knime.

the class TreeNumericColumnData method updateChildMemberships.

@Override
public BitSet updateChildMemberships(final TreeNodeCondition childCondition, final DataMemberships parentMemberships) {
    final TreeNodeNumericCondition numCondition = (TreeNodeNumericCondition) childCondition;
    final NumericOperator numOperator = numCondition.getNumericOperator();
    final double splitValue = numCondition.getSplitValue();
    final ColumnMemberships columnMemberships = parentMemberships.getColumnMemberships(getMetaData().getAttributeIndex());
    columnMemberships.reset();
    final BitSet inChild = new BitSet(columnMemberships.size());
    int startIndex = 0;
    // }
    if (!columnMemberships.nextIndexFrom(startIndex)) {
        throw new IllegalStateException("The current columnMemberships object contains no element that satisfies the splitcondition");
    }
    final int lengthNonMissing = getLengthNonMissing();
    do {
        final double value = getSorted(columnMemberships.getIndexInColumn());
        boolean matches;
        switch(numOperator) {
            case LessThanOrEqual:
                matches = value <= splitValue;
                break;
            case LargerThan:
                matches = value > splitValue;
                break;
            case LessThanOrEqualOrMissing:
                matches = Double.isNaN(value) ? true : value <= splitValue;
                break;
            case LargerThanOrMissing:
                matches = Double.isNaN(value) ? true : value > splitValue;
                break;
            default:
                throw new IllegalStateException("Unknown operator " + numOperator);
        }
        if (matches) {
            inChild.set(columnMemberships.getIndexInDataMemberships());
        }
    } while (columnMemberships.next() && columnMemberships.getIndexInColumn() < lengthNonMissing);
    // reached end of columnMemberships
    if (columnMemberships.getIndexInColumn() < lengthNonMissing) {
        return inChild;
    }
    // handle missing values
    if (numOperator.equals(NumericOperator.LessThanOrEqualOrMissing) || numOperator.equals(NumericOperator.LargerThanOrMissing) || numCondition.acceptsMissings()) {
        do {
            inChild.set(columnMemberships.getIndexInDataMemberships());
        } while (columnMemberships.next());
    }
    return inChild;
}

Example 8 with TreeNodeCondition

use of org.knime.base.node.mine.treeensemble2.model.TreeNodeCondition in project knime-core by knime.

the class Surrogates method calculateSurrogates.

/**
 * This function finds the splits (in <b>candidates</b>) that best mirror the best split (<b>candidates[0]</b>). The
 * splits are compared to the so called <i>majority split</i> that sends all records to the child that the most rows
 * in the best split are sent to. This <i>majority split</i> is also always the last surrogate to guarantee that
 * every record is sent to a child even if all surrogate attributes are also missing.
 *
 * @param dataMemberships
 * @param candidates the first candidate must be the best split
 * @return A SplitCandidate containing surrogates
 */
public static SurrogateSplit calculateSurrogates(final DataMemberships dataMemberships, final SplitCandidate[] candidates) {
    final SplitCandidate bestSplit = candidates[0];
    TreeAttributeColumnData bestSplitCol = bestSplit.getColumnData();
    TreeNodeCondition[] bestSplitChildConditions = bestSplit.getChildConditions();
    if (bestSplitChildConditions.length != 2) {
        throw new IllegalArgumentException("Surrogates can only be calculated for binary splits.");
    }
    BitSet bestSplitLeft = bestSplitCol.updateChildMemberships(bestSplitChildConditions[0], dataMemberships);
    BitSet bestSplitRight = bestSplitCol.updateChildMemberships(bestSplitChildConditions[1], dataMemberships);
    final double numRowsInNode = dataMemberships.getRowCount();
    // probability for a row to be in the current node
    final double probInNode = numRowsInNode / dataMemberships.getRowCountInRoot();
    // probability for a row to go left according to the best split
    final double bestSplitProbLeft = bestSplitLeft.cardinality() / numRowsInNode;
    // probability for a row to go right according to the best split
    final double bestSplitProbRight = bestSplitRight.cardinality() / numRowsInNode;
    // the majority rule is always the last surrogate and defines a default direction if all other
    // surrogates fail
    final boolean majorityGoesLeft = bestSplitProbRight > bestSplitProbLeft ? false : true;
    // see calculatAssociationMeasure() for more information
    final double errorMajorityRule = majorityGoesLeft ? bestSplitProbRight : bestSplitProbLeft;
    // stores association measure for candidates
    ArrayList<SurrogateCandidate> surrogateCandidates = new ArrayList<SurrogateCandidate>();
    for (int i = 1; i < candidates.length; i++) {
        SplitCandidate surrogate = candidates[i];
        TreeAttributeColumnData surrogateCol = surrogate.getColumnData();
        TreeNodeCondition[] surrogateChildConditions = surrogate.getChildConditions();
        if (surrogateChildConditions.length != 2) {
            throw new IllegalArgumentException("Surrogates can only be calculated for binary splits.");
        }
        BitSet surrogateLeft = surrogateCol.updateChildMemberships(surrogateChildConditions[0], dataMemberships);
        BitSet surrogateRight = surrogateCol.updateChildMemberships(surrogateChildConditions[1], dataMemberships);
        BitSet bothLeft = (BitSet) bestSplitLeft.clone();
        bothLeft.and(surrogateLeft);
        BitSet bothRight = (BitSet) bestSplitRight.clone();
        bothRight.and(surrogateRight);
        // the complement of a split (switching the children) has the same gain value as the original split
        BitSet complementBothLeft = (BitSet) bestSplitLeft.clone();
        complementBothLeft.and(surrogateRight);
        BitSet complementBothRight = (BitSet) bestSplitRight.clone();
        complementBothRight.and(surrogateLeft);
        // calculating the probability that the surrogate candidate and the best split send a case both in the same
        // direction is necessary because there might be missing values which are not send in either direction
        double probBothLeft = (bothLeft.cardinality() / numRowsInNode);
        double probBothRight = (bothRight.cardinality() / numRowsInNode);
        // the relative probability that the surrogate predicts the best split correctly
        double predictProb = probBothLeft + probBothRight;
        double probComplementBothLeft = (complementBothLeft.cardinality() / numRowsInNode);
        double probComplementBothRight = (complementBothRight.cardinality() / numRowsInNode);
        double complementPredictProb = probComplementBothLeft + probComplementBothRight;
        double associationMeasure = calculateAssociationMeasure(errorMajorityRule, predictProb);
        double complementAssociationMeasure = calculateAssociationMeasure(errorMajorityRule, complementPredictProb);
        boolean useComplement = complementAssociationMeasure > associationMeasure ? true : false;
        double betterAssociationMeasure = useComplement ? complementAssociationMeasure : associationMeasure;
        assert betterAssociationMeasure <= 1 : "Association measure can not be greater than 1.";
        if (betterAssociationMeasure > 0) {
            BitSet[] childMarkers = new BitSet[] { surrogateLeft, surrogateRight };
            surrogateCandidates.add(new SurrogateCandidate(surrogate, useComplement, betterAssociationMeasure, childMarkers));
        }
    }
    BitSet[] childMarkers = new BitSet[] { bestSplitLeft, bestSplitRight };
    // if there are no surrogates, create condition with default rule as only surrogate
    if (surrogateCandidates.isEmpty()) {
        fillInMissingChildMarkers(bestSplit, childMarkers, surrogateCandidates, majorityGoesLeft);
        return new SurrogateSplit(new AbstractTreeNodeSurrogateCondition[] { new TreeNodeSurrogateOnlyDefDirCondition((TreeNodeColumnCondition) bestSplitChildConditions[0], majorityGoesLeft), new TreeNodeSurrogateOnlyDefDirCondition((TreeNodeColumnCondition) bestSplitChildConditions[1], !majorityGoesLeft) }, childMarkers);
    }
    surrogateCandidates.sort(null);
    int condSize = surrogateCandidates.size() + 1;
    TreeNodeColumnCondition[] conditionsLeftChild = new TreeNodeColumnCondition[condSize];
    TreeNodeColumnCondition[] conditionsRightChild = new TreeNodeColumnCondition[condSize];
    conditionsLeftChild[0] = (TreeNodeColumnCondition) bestSplitChildConditions[0];
    conditionsRightChild[0] = (TreeNodeColumnCondition) bestSplitChildConditions[1];
    for (int i = 0; i < surrogateCandidates.size(); i++) {
        SurrogateCandidate surrogateCandidate = surrogateCandidates.get(i);
        TreeNodeCondition[] surrogateConditions = surrogateCandidate.getSplitCandidate().getChildConditions();
        if (surrogateCandidate.m_useComplement) {
            conditionsLeftChild[i + 1] = (TreeNodeColumnCondition) surrogateConditions[1];
            conditionsRightChild[i + 1] = (TreeNodeColumnCondition) surrogateConditions[0];
        } else {
            conditionsLeftChild[i + 1] = (TreeNodeColumnCondition) surrogateConditions[0];
            conditionsRightChild[i + 1] = (TreeNodeColumnCondition) surrogateConditions[1];
        }
    }
    // check if there are any rows missing in the best split
    if (!bestSplit.getMissedRows().isEmpty()) {
        // fill in any missing child markers
        fillInMissingChildMarkers(bestSplit, childMarkers, surrogateCandidates, majorityGoesLeft);
    }
    return new SurrogateSplit(new TreeNodeSurrogateCondition[] { new TreeNodeSurrogateCondition(conditionsLeftChild, majorityGoesLeft), new TreeNodeSurrogateCondition(conditionsRightChild, !majorityGoesLeft) }, childMarkers);
}

Example 9 with TreeNodeCondition

use of org.knime.base.node.mine.treeensemble2.model.TreeNodeCondition in project knime-core by knime.

the class Surrogates method createSurrogateSplitWithDefaultDirection.

/**
 * Creates a surrogate split that only contains the best split and the default (majority) direction. It does
 * <b>NOT</b> calculate any surrogate splits (and is therefore more efficient).
 *
 * @param dataMemberships
 * @param bestSplit
 * @return SurrogateSplit with conditions for both children. The conditions only contain the condition for the best
 *         split and the default condition (true for the child the most records go to and false for the other one).
 */
public static SurrogateSplit createSurrogateSplitWithDefaultDirection(final DataMemberships dataMemberships, final SplitCandidate bestSplit) {
    TreeAttributeColumnData col = bestSplit.getColumnData();
    TreeNodeCondition[] conditions = bestSplit.getChildConditions();
    // get child marker for best split
    BitSet left = col.updateChildMemberships(conditions[0], dataMemberships);
    BitSet right = col.updateChildMemberships(conditions[1], dataMemberships);
    // decide which child the majority of the records goes to
    boolean majorityGoesLeft = left.cardinality() < right.cardinality() ? false : true;
    // create surrogate conditions
    TreeNodeSurrogateOnlyDefDirCondition condLeft = new TreeNodeSurrogateOnlyDefDirCondition((TreeNodeColumnCondition) conditions[0], majorityGoesLeft);
    TreeNodeSurrogateOnlyDefDirCondition condRight = new TreeNodeSurrogateOnlyDefDirCondition((TreeNodeColumnCondition) conditions[1], !majorityGoesLeft);
    BitSet[] childMarkers = new BitSet[] { left, right };
    fillInMissingChildMarkersWithDefault(bestSplit, childMarkers, majorityGoesLeft);
    return new SurrogateSplit(new AbstractTreeNodeSurrogateCondition[] { condLeft, condRight }, new BitSet[] { left, right });
}

Example 10 with TreeNodeCondition

use of org.knime.base.node.mine.treeensemble2.model.TreeNodeCondition in project knime-core by knime.

the class TreeNumericColumnDataTest method testUpdateChildMemberships.

/**
 * Tests the {@link TreeNumericColumnData#updateChildMemberships(TreeNodeCondition, DataMemberships)} methods with
 * different conditions including missing values.
 *
 * @throws Exception
 */
@Test
public void testUpdateChildMemberships() throws Exception {
    final TreeEnsembleLearnerConfiguration config = createConfig();
    final TestDataGenerator dataGen = new TestDataGenerator(config);
    final int[] indices = new int[] { 0, 1, 2, 3, 4, 5, 6 };
    final double[] weights = new double[7];
    Arrays.fill(weights, 1.0);
    final DataMemberships dataMem = new MockDataColMem(indices, indices, weights);
    final String noMissingsCSV = "-50, -3, -2, 2, 25, 100, 101";
    final TreeNumericColumnData col = dataGen.createNumericAttributeColumn(noMissingsCSV, "noMissings-col", 0);
    // less than or equals
    TreeNodeNumericCondition numCond = new TreeNodeNumericCondition(col.getMetaData(), -2, NumericOperator.LessThanOrEqual, false);
    BitSet inChild = col.updateChildMemberships(numCond, dataMem);
    BitSet expected = new BitSet(3);
    expected.set(0, 3);
    assertEquals("The produced BitSet is incorrect.", expected, inChild);
    // greater than
    numCond = new TreeNodeNumericCondition(col.getMetaData(), 10, NumericOperator.LargerThan, false);
    inChild = col.updateChildMemberships(numCond, dataMem);
    expected.clear();
    expected.set(4, 7);
    assertEquals("The produced BitSet is incorrect", expected, inChild);
    // with missing values
    final String missingsCSV = "-2, 0, 1, 43, 61, 66, NaN";
    final TreeNumericColumnData colWithMissings = dataGen.createNumericAttributeColumn(missingsCSV, "missings-col", 0);
    // less than or equal or missing
    numCond = new TreeNodeNumericCondition(colWithMissings.getMetaData(), 12, NumericOperator.LessThanOrEqual, true);
    inChild = colWithMissings.updateChildMemberships(numCond, dataMem);
    expected.clear();
    expected.set(0, 3);
    expected.set(6);
    assertEquals("The produced BitSet is incorrect", expected, inChild);
    // less than or equals not missing
    numCond = new TreeNodeNumericCondition(colWithMissings.getMetaData(), 12, NumericOperator.LessThanOrEqual, false);
    inChild = colWithMissings.updateChildMemberships(numCond, dataMem);
    expected.clear();
    expected.set(0, 3);
    assertEquals("The produced BitSet is incorrect", expected, inChild);
    // larger than or missing
    numCond = new TreeNodeNumericCondition(colWithMissings.getMetaData(), 43, NumericOperator.LargerThan, true);
    inChild = colWithMissings.updateChildMemberships(numCond, dataMem);
    expected.clear();
    expected.set(4, 7);
    assertEquals("The produced BitSet is incorrect", expected, inChild);
    // larger than not missing
    numCond = new TreeNodeNumericCondition(colWithMissings.getMetaData(), 12, NumericOperator.LargerThan, false);
    inChild = colWithMissings.updateChildMemberships(numCond, dataMem);
    expected.clear();
    expected.set(3, 6);
    assertEquals("The produced BitSet is incorrect", expected, inChild);
}