Package

weka.classifiers.rules

Synopsis

Class for generating a PART decision list. Uses separate-and-conquer. Builds a partial C4.5 decision tree in each iteration and makes the "best" leaf into a rule.

For more information, see:

Eibe Frank, Ian H. Witten: Generating Accurate Rule Sets Without Global Optimization. In: Fifteenth International Conference on Machine Learning, 144-151, 1998.

Options

The table below describes the options available for PART.

Option	Description
binarySplits	Whether to use binary splits on nominal attributes when building the partial trees.
confidenceFactor	The confidence factor used for pruning (smaller values incur more pruning).
debug	If set to true, classifier may output additional info to the console.
minNumObj	The minimum number of instances per rule.
numFolds	Determines the amount of data used for reduced-error pruning. One fold is used for pruning, the rest for growing the rules.
reducedErrorPruning	Whether reduced-error pruning is used instead of C.4.5 pruning.
seed	The seed used for randomizing the data when reduced-error pruning is used.
unpruned	Whether pruning is performed.

Capabilities

The table below describes the capabilites of PART.

Capability	Supported
Class	Missing class values, Binary class, Nominal class
Attributes	Numeric attributes, Empty nominal attributes, Date attributes, Unary attributes, Binary attributes, Nominal attributes, Missing values
Min # of instances	1

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