Package

weka.classifiers.bayes

Synopsis

Class for building and using a Complement class Naive Bayes classifier.

For more information see,

Jason D. Rennie, Lawrence Shih, Jaime Teevan, David R. Karger: Tackling the Poor Assumptions of Naive Bayes Text Classifiers. In: ICML, 616-623, 2003.

P.S.: TF, IDF and length normalization transforms, as described in the paper, can be performed through weka.filters.unsupervised.StringToWordVector.

Options

The table below describes the options available for ComplementNaiveBayes.

Option

Description

debug

If set to true, classifier may output additional info to the console.

normalizeWordWeights

Normalizes the word weights for each class.

smoothingParameter

Sets the smoothing parameter to avoid zero WordGivenClass probabilities (default=1.0).

Capabilities

The table below describes the capabilites of ComplementNaiveBayes.

Capability

Supported

Class

Nominal class, Missing class values, Binary class

Attributes

Missing values, Numeric attributes

Min # of instances

1