|
Class Summary |
| BinC45ModelSelection |
Class for selecting a C4.5-like binary (!) split for a given dataset. |
| BinC45Split |
Class implementing a binary C4.5-like split on an attribute. |
| C45ModelSelection |
Class for selecting a C4.5-type split for a given dataset. |
| C45PruneableClassifierTree |
Class for handling a tree structure that can
be pruned using C4.5 procedures. |
| C45PruneableDecList |
Class for handling a partial tree structure pruned using C4.5's
pruning heuristic. |
| C45Split |
Class implementing a C4.5-type split on an attribute. |
| ClassifierDecList |
Class for handling a rule (partial tree) for a decision list. |
| ClassifierSplitModel |
Abstract class for classification models that can be used
recursively to split the data. |
| ClassifierTree |
Class for handling a tree structure used for
classification. |
| Distribution |
Class for handling a distribution of class values. |
| EntropyBasedSplitCrit |
"Abstract" class for computing splitting criteria
based on the entropy of a class distribution. |
| EntropySplitCrit |
Class for computing the entropy for a given distribution. |
| GainRatioSplitCrit |
Class for computing the gain ratio for a given distribution. |
| InfoGainSplitCrit |
Class for computing the information gain for a given distribution. |
| J48 |
Class for generating an unpruned or a pruned C4.5 decision tree. |
| MakeDecList |
Class for handling a decision list. |
| ModelSelection |
Abstract class for model selection criteria. |
| NoSplit |
Class implementing a "no-split"-split. |
| PART |
Class for generating a PART decision list. |
| PruneableClassifierTree |
Class for handling a tree structure that can
be pruned using a pruning set. |
| PruneableDecList |
Class for handling a partial tree structure that
can be pruned using a pruning set. |
| SplitCriterion |
Abstract class for computing splitting criteria
with respect to distributions of class values. |
| Stats |
Class implementing a statistical routine needed by J48. |