org.knime.base.node.mine.decisiontree2.model
Class DecisionTreeNodeSplitPMML

java.lang.Object
  org.knime.base.node.mine.decisiontree2.model.DecisionTreeNode
      org.knime.base.node.mine.decisiontree2.model.DecisionTreeNodeSplit
          org.knime.base.node.mine.decisiontree2.model.DecisionTreeNodeSplitPMML

All Implemented Interfaces:

Serializable, TreeNode

public class DecisionTreeNodeSplitPMML
extends DecisionTreeNodeSplit

Decision tree split node that supports PMML predicates to partition the data. An arbitrary number of childs (>2) is allowed.

Author:

Dominik Morent, KNIME.com, Zurich, Switzerland

See Also:

Serialized Form

Constructor Summary

DecisionTreeNodeSplitPMML()

DecisionTreeNodeSplitPMML(int nodeId, DataCell majorityClass, LinkedHashMap<DataCell,Double> classCounts, String splitAttribute, PMMLPredicate[] splitPredicates, DecisionTreeNode[] children)
Constructor of base class.

DecisionTreeNodeSplitPMML(int nodeId, DataCell majorityClass, LinkedHashMap<DataCell,Double> classCounts, String splitAttribute, PMMLPredicate[] splitPredicates, DecisionTreeNode[] children, int defaultChild)
Constructor of base class.

Method Summary

void	addCoveredColor(DataCell cell, DataRow row, DataTableSpec spec, double weight) Add colors for patterns given as a row of values if they fall within a specific node.
void	addCoveredPattern(DataCell cell, DataRow row, DataTableSpec spec, double weight) Add patterns given as a row of values if they fall within a specific node.
Set<RowKey>	coveredPattern()
LinkedHashMap<DataCell,Double>	getClassCounts(DataCell cell, DataRow row, DataTableSpec spec) Determine class counts for a new pattern given as a row of values.
LinkedHashMap<DataCell,Double>	getClassCounts(DataRow row, DataTableSpec spec) Determine class counts for a new pattern given as a row of values.
DecisionTreeNode	getDefaultChild()
int	getDefaultChildIndex()
PMMLPredicate[]	getSplitPred() Returns the split predicate array of this node.
String	getStringSummary()
void	loadNodeSplitInternalsFromPredParams(ModelContentRO pConf) Load internal SplitNode settings from a ModelContent object.
void	saveNodeSplitInternalsToPredParams(ModelContentWO pConf) save internal SplitNode settings to a ModelContent object.
void	setDefaultChild(int defaultChild)

Methods inherited from class org.knime.base.node.mine.decisiontree2.model.DecisionTreeNodeSplit

addCoveredColor, addCoveredPattern, addNode, addNodeToTreeDepthFirst, children, getAllowsChildren, getChildAt, getChildCount, getChildNodeAt, getChildren, getCountOfSubtree, getIndex, getMVStrategy, getNodeClassWeights, getNTCStrategy, getSplitAttr, isLeaf, loadNodeInternalsFromPredParams, makeRoomForKids, replaceChild, saveNodeInternalsToPredParams, setChildNodeIndex, setMVStrategy, setNTCStrategy

Methods inherited from class org.knime.base.node.mine.decisiontree2.model.DecisionTreeNode

addColorToMap, coveredColors, createNewNode, createNodeFromPredictorParams, getClassCounts, getCustomData, getEntireClassCount, getMajorityClass, getOverallColorCount, getOwnClassCount, getOwnIndex, getParent, getPrefix, getWinnerAndClasscounts, loadFromPredictorParams, newColors, resetColorInformation, saveToPredictorParams, setCoveredColors, setCustomData, setParent, setPrefix, toString

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Constructor Detail

DecisionTreeNodeSplitPMML

public DecisionTreeNodeSplitPMML()

DecisionTreeNodeSplitPMML

public DecisionTreeNodeSplitPMML(int nodeId,
                                 DataCell majorityClass,
                                 LinkedHashMap<DataCell,Double> classCounts,
                                 String splitAttribute,
                                 PMMLPredicate[] splitPredicates,
                                 DecisionTreeNode[] children)

Constructor of base class. The necessary data is provided directly in the constructor.

Parameters:

nodeId - the id of this node

majorityClass - the majority class of the records in this node

classCounts - the class distribution of the data in this node

splitAttribute - the attribute name on which to split

splitPredicates - the split predicates used to partition the data

children - the children split according to the split values

DecisionTreeNodeSplitPMML

public DecisionTreeNodeSplitPMML(int nodeId,
                                 DataCell majorityClass,
                                 LinkedHashMap<DataCell,Double> classCounts,
                                 String splitAttribute,
                                 PMMLPredicate[] splitPredicates,
                                 DecisionTreeNode[] children,
                                 int defaultChild)

Constructor of base class. The necessary data is provided directly in the constructor.

Parameters:

nodeId - the id of this node

majorityClass - the majority class of the records in this node

classCounts - the class distribution of the data in this node

splitAttribute - the attribute name on which to split

splitPredicates - the split predicates used to partition the data

children - the children split according to the split values

defaultChild - index of the default child (only evaluated with PMMLMissingValueStrategy DEFAULT_CHILD

Method Detail

getDefaultChild

public DecisionTreeNode getDefaultChild()

Returns:

the defaultChild

getDefaultChildIndex

public int getDefaultChildIndex()

Returns:

the defaultChild index

setDefaultChild

public void setDefaultChild(int defaultChild)

Parameters:

defaultChild - the defaultChild to set

getClassCounts

public LinkedHashMap<DataCell,Double> getClassCounts(DataRow row,
                                                     DataTableSpec spec)

Determine class counts for a new pattern given as a row of values. Returns a HashMap listing counts for all classes.

Overrides:

getClassCounts in class DecisionTreeNodeSplit

Parameters:

row - input pattern

spec - the corresponding table spec

Returns:

HashMap class/count

getClassCounts

public LinkedHashMap<DataCell,Double> getClassCounts(DataCell cell,
                                                     DataRow row,
                                                     DataTableSpec spec)

Determine class counts for a new pattern given as a row of values. Returns a HashMap listing counts for all classes.

Specified by:

getClassCounts in class DecisionTreeNodeSplit

Parameters:

cell - the call to be used for classification at this node

row - input pattern

spec - the corresponding table spec

Returns:

HashMap class/count

addCoveredPattern

public void addCoveredPattern(DataCell cell,
                              DataRow row,
                              DataTableSpec spec,
                              double weight)
                       throws Exception

Add patterns given as a row of values if they fall within a specific node. Usually only Leafs will actually hold a list of RowKeys, all intermediate nodes will collect "their" information recursively.

Specified by:

addCoveredPattern in class DecisionTreeNodeSplit

Parameters:

cell - the cell to be used for classification at this node

row - input pattern

spec - the corresponding table spec

weight - the weight of this row (between 0.0 and 1.0)

Throws:

Exception - if something went wrong (unknown attribute for example)

addCoveredColor

public void addCoveredColor(DataCell cell,
                            DataRow row,
                            DataTableSpec spec,
                            double weight)
                     throws Exception

Add colors for patterns given as a row of values if they fall within a specific node.

Specified by:

addCoveredColor in class DecisionTreeNodeSplit

Parameters:

cell - the call to be used for classification at this node

row - input pattern

spec - the corresponding table spec

weight - the weight of this row (between 0.0 and 1.0)

Throws:

Exception - if something went wrong (unknown attribute for example)

coveredPattern

public Set<RowKey> coveredPattern()

Specified by:

coveredPattern in class DecisionTreeNodeSplit

Returns:

set of data cells which are the row keys that are covered by all nodes of this branch

loadNodeSplitInternalsFromPredParams

public void loadNodeSplitInternalsFromPredParams(ModelContentRO pConf)
                                          throws InvalidSettingsException

Load internal SplitNode settings from a ModelContent object.

Specified by:

loadNodeSplitInternalsFromPredParams in class DecisionTreeNodeSplit

Parameters:

pConf - configuration object to load decision tree from.

Throws:

InvalidSettingsException - if something goes wrong

saveNodeSplitInternalsToPredParams

public void saveNodeSplitInternalsToPredParams(ModelContentWO pConf)

save internal SplitNode settings to a ModelContent object.

Specified by:

saveNodeSplitInternalsToPredParams in class DecisionTreeNodeSplit

Parameters:

pConf - configuration object to save decision tree to

getStringSummary

public String getStringSummary()

Specified by:

getStringSummary in class DecisionTreeNode

Returns:

string summary of node content (split, leaf info...)

getSplitPred

public PMMLPredicate[] getSplitPred()

Returns the split predicate array of this node.

Returns:

the split predicate array of this node