Package
weka.classifiers.trees
Synopsis
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.
Options
The table below describes the options available for J48.
Option | Description |
|---|---|
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 | If set to true, classifier may output additional info to the console. |
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. |
useLaplace | Whether counts at leaves are smoothed based on Laplace. |
Capabilities
The table below describes the capabilites of J48.
Capability | Supported |
|---|---|
Class | Nominal class, Missing class values, Binary class |
Attributes | Missing values, Numeric attributes, Unary attributes, Date attributes, Binary attributes, Empty nominal attributes, Nominal attributes |
Min # of instances | 0 |