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J48 (Weka)

DeprecatedKNIME WEKA nodes version 2.7.3.v201905311239 by KNIME AG, Zurich, Switzerland

Class for generating a pruned or unpruned C4.5 decision tree. For more information, see Ross Quinlan (1993). "C4.5: Programs for Machine Learning", Morgan Kaufmann Publishers, San Mateo, CA. Use this node to build a DecisionTree model that can later be used by the DecisionTreePredictor node. The view provides a visual model of the DecisionTree as well as some statistical output (number of nodes and leaves).

Options

binarySplits
Whether to use binary splits on nominal attributes when building the trees.
confidenceFactor
The confidence factor used for pruning (smaller values incur more pruning).
debug
The value of this option is ignored in Knime.
minNumObj
The minimum number of instances per leaf.
numFolds
Determines the amount of data used for reduced-error pruning. One fold is used for pruning, the rest for growing the tree.
reducedErrorPruning
Whether reduced-error pruning is used instead of C.4.5 pruning.
saveInstanceData
Whether to save the training data for visualization.
seed
The seed used for randomizing the data when reduced-error pruning is used.
subtreeRaising
Whether to consider the subtree raising operation when pruning.
unpruned
Whether pruning is performed. (Due to an issue in the weka code, once this option is set to true, the reducedErrorPruning can not be changed anymore)
useLaplace
Whether counts at leaves are smoothed based on Laplace.

Input Ports

Training data

Output Ports

PMML Decision Tree Model

Views

Decision Tree View
The Decision Tree view provides a tree view of KNIME in addition to the tree view of weka and some summary information.

Installation

To use this node in KNIME, install KNIME WEKA nodes from the following update site:

KNIME 4.0
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