Examples with DecisionTreeNode org.knime.base.node.mine.decisiontree2.model.DecisionTreeNode used on opensource projects

Example 6 with DecisionTreeNode

use of org.knime.base.node.mine.decisiontree2.model.DecisionTreeNode in project knime-core by knime.

the class TreeEnsembleLearnerNodeView method getSubtree.

private List<DecisionTreeNode> getSubtree(final DecisionTreeNode node) {
    List<DecisionTreeNode> subTree = new ArrayList<DecisionTreeNode>();
    List<DecisionTreeNode> toProcess = new LinkedList<DecisionTreeNode>();
    toProcess.add(0, node);
    // Traverse the tree breadth first
    while (!toProcess.isEmpty()) {
        DecisionTreeNode curr = toProcess.remove(0);
        subTree.add(curr);
        for (int i = 0; i < curr.getChildCount(); i++) {
            toProcess.add(0, curr.getChildAt(i));
        }
    }
    return subTree;
}

Example 7 with DecisionTreeNode

use of org.knime.base.node.mine.decisiontree2.model.DecisionTreeNode in project knime-core by knime.

the class TreeEnsembleLearnerNodeView method createTreeMenu.

/**
 * Create menu to control tree.
 *
 * @return A new JMenu with tree operation buttons
 */
private JMenu createTreeMenu() {
    final JMenu result = new JMenu("Tree");
    result.setMnemonic('T');
    Action expand = new ExpandBranchAction<DecisionTreeNode>(m_graph);
    expand.putValue(Action.NAME, "Expand Selected Branch");
    Action collapse = new CollapseBranchAction<DecisionTreeNode>(m_graph);
    collapse.putValue(Action.NAME, "Collapse Selected Branch");
    result.add(expand);
    result.add(collapse);
    return result;
}

Example 8 with DecisionTreeNode

use of org.knime.base.node.mine.decisiontree2.model.DecisionTreeNode in project knime-core by knime.

the class TreeEnsembleLearnerNodeView method updateHiLite.

// ///////////////////////////////////////////////////
private void updateHiLite(final boolean state) {
    DecisionTreeNode selected = m_graph.getSelected();
    if (selected == null) {
        return;
    }
    Set<RowKey> covPat = new HashSet<RowKey>();
    covPat.addAll(selected.coveredPattern());
    if (state) {
        m_hiLiteHdl.fireHiLiteEvent(covPat);
    } else {
        m_hiLiteHdl.fireUnHiLiteEvent(covPat);
    }
}

Example 9 with DecisionTreeNode

use of org.knime.base.node.mine.decisiontree2.model.DecisionTreeNode in project knime-core by knime.

the class TreeEnsembleLearnerNodeView method recreateHiLite.

private void recreateHiLite() {
    HiLiteHandler handler = m_hiLiteHdl;
    if (handler == null) {
        return;
    }
    Set<RowKey> hilited = handler.getHiLitKeys();
    Set<DecisionTreeNode> toHilite = new HashSet<DecisionTreeNode>();
    DecisionTreeNode root = m_graph.getRootNode();
    List<DecisionTreeNode> toProcess = new LinkedList<DecisionTreeNode>();
    if (null != root) {
        toProcess.add(0, root);
    }
    // Traverse the tree breadth first
    while (!toProcess.isEmpty()) {
        DecisionTreeNode curr = toProcess.remove(0);
        // cover any pattern
        if (curr.coveredPattern().isEmpty()) {
            continue;
        }
        if (hilited.containsAll(curr.coveredPattern())) {
            // hilite subtree starting from curr
            toHilite.addAll(getSubtree(curr));
        } else {
            for (int i = 0; i < curr.getChildCount(); i++) {
                toProcess.add(0, curr.getChildAt(i));
            }
        }
    }
    m_graph.hiLite(toHilite);
}

Example 10 with DecisionTreeNode

use of org.knime.base.node.mine.decisiontree2.model.DecisionTreeNode in project knime-core by knime.

the class TreeNodeRegression method createDecisionTreeNode.

/**
 * @param metaData
 * @return
 */
public DecisionTreeNode createDecisionTreeNode(final MutableInteger idGenerator, final TreeMetaData metaData) {
    DataCell majorityCell = new StringCell(DoubleFormat.formatDouble(m_mean));
    final int nrChildren = getNrChildren();
    LinkedHashMap<DataCell, Double> distributionMap = new LinkedHashMap<DataCell, Double>();
    distributionMap.put(majorityCell, m_totalSum);
    if (nrChildren == 0) {
        return new DecisionTreeNodeLeaf(idGenerator.inc(), majorityCell, distributionMap);
    } else {
        int id = idGenerator.inc();
        DecisionTreeNode[] childNodes = new DecisionTreeNode[nrChildren];
        int splitAttributeIndex = getSplitAttributeIndex();
        assert splitAttributeIndex >= 0 : "non-leaf node has no split";
        String splitAttribute = metaData.getAttributeMetaData(splitAttributeIndex).getAttributeName();
        PMMLPredicate[] childPredicates = new PMMLPredicate[nrChildren];
        for (int i = 0; i < nrChildren; i++) {
            final TreeNodeRegression treeNode = getChild(i);
            TreeNodeCondition cond = treeNode.getCondition();
            childPredicates[i] = cond.toPMMLPredicate();
            childNodes[i] = treeNode.createDecisionTreeNode(idGenerator, metaData);
        }
        return new DecisionTreeNodeSplitPMML(id, majorityCell, distributionMap, splitAttribute, childPredicates, childNodes);
    }
}