DTNB
Package
weka.classifiers.rules
Synopsis
Class for building and using a decision table/naive bayes hybrid classifier. At each point in the search, the algorithm evaluates the merit of dividing the attributes into two disjoint subsets: one for the decision table, the other for naive Bayes. A forward selection search is used, where at each step, selected attributes are modeled by naive Bayes and the remainder by the decision table, and all attributes are modelled by the decision table initially. At each step, the algorithm also considers dropping an attribute entirely from the model.
For more information, see:
Mark Hall, Eibe Frank: Combining Naive Bayes and Decision Tables. In: Proceedings of the 21st Florida Artificial Intelligence Society Conference (FLAIRS), ?-?, 2008.
Available in Weka 3.6.x - 3.7.1. Available via the package management system for Weka >= 3.7.2 (DTNB)
Options
The table below describes the options available for DTNB.
Option |
Description |
|---|---|
crossVal |
Sets the number of folds for cross validation (1 = leave one out). |
debug |
If set to true, classifier may output additional info to the console. |
displayRules |
Sets whether rules are to be printed. |
evaluationMeasure |
The measure used to evaluate the performance of attribute combinations used in the decision table. |
search |
The search method used to find good attribute combinations for the decision table. |
useIBk |
Sets whether IBk should be used instead of the majority class. |
Capabilities
The table below describes the capabilites of DTNB.
Capability |
Supported |
|---|---|
Class |
Nominal class, Missing class values, Binary class |
Attributes |
Nominal attributes, Missing values, Date attributes, Empty nominal attributes, Numeric attributes, Unary attributes, Binary attributes |
Min # of instances |
1 |