PART
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 |