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Package

weka.classifiers.bayes

Synopsis

Class for a Naive Bayes classifier using estimator classes. This is the updateable version of NaiveBayes.
This classifier will use a default precision of 0.1 for numeric attributes when buildClassifier is called with zero training instances.

For more information on Naive Bayes classifiers, see

George H. John, Pat Langley: Estimating Continuous Distributions in Bayesian Classifiers. In: Eleventh Conference on Uncertainty in Artificial Intelligence, San Mateo, 338-345, 1995.

Options

The table below describes the options available for NaiveBayesUpdateable.

Option

Description

debug

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

displayModelInOldFormat

Use old format for model output. The old format is better when there are many class values. The new format is better when there are fewer classes and many attributes.

useKernelEstimator

Use a kernel estimator for numeric attributes rather than a normal distribution.

useSupervisedDiscretization

Use supervised discretization to convert numeric attributes to nominal ones.

Capabilities

The table below describes the capabilites of NaiveBayesUpdateable.

Capability

Supported

Class

Missing class values, Binary class, Nominal class

Attributes

Unary attributes, Nominal attributes, Missing values, Numeric attributes, Empty nominal attributes, Binary attributes

Min # of instances

0

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