# Package weka.classifiers.rules

package weka.classifiers.rules

Related Packages
Package
Description
weka.classifiers
weka.classifiers.rules.part
Classes
Class
Description
ConjunctiveRule
This class implements a single conjunctive rule learner that can predict for numeric and nominal class labels.
A rule consists of antecedents "AND"ed together and the consequent (class value) for the classification/regression.
DecisionTable
Class for building and using a simple decision table majority classifier.
For more information see:
Ron Kohavi: The Power of Decision Tables.
DecisionTableHashKey
Class providing hash table keys for DecisionTable
DTNB
Class for building and using a decision table/naive bayes hybrid classifier.
JRip
This class implements a propositional rule learner, Repeated Incremental Pruning to Produce Error Reduction (RIPPER), which was proposed by William W.
M5Rules
Generates a decision list for regression problems using separate-and-conquer.
NNge
Nearest-neighbor-like algorithm using non-nested generalized exemplars (which are hyperrectangles that can be viewed as if-then rules).
OneR
Class for building and using a 1R classifier; in other words, uses the minimum-error attribute for prediction, discretizing numeric attributes.
PART
Class for generating a PART decision list.
Prism
Class for building and using a PRISM rule set for classification.
Ridor
An implementation of a RIpple-DOwn Rule learner.
It generates a default rule first and then the exceptions for the default rule with the least (weighted) error rate.
Rule
Abstract class of generic rule
RuleStats
This class implements the statistics functions used in the propositional rule learner, from the simpler ones like count of true/false positive/negatives, filter data based on the ruleset, etc.
ZeroR
Class for building and using a 0-R classifier.