NaiveBayesUpdateable
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 |