weka.classifiers.bayes
Class NaiveBayesUpdateable
java.lang.Object
weka.classifiers.Classifier
weka.classifiers.DistributionClassifier
weka.classifiers.bayes.NaiveBayes
weka.classifiers.bayes.NaiveBayesUpdateable
- All Implemented Interfaces:
- java.lang.Cloneable, OptionHandler, java.io.Serializable, UpdateableClassifier, WeightedInstancesHandler
- public class NaiveBayesUpdateable
- extends NaiveBayes
- implements UpdateableClassifier
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 and Pat Langley (1995). Estimating
Continuous Distributions in Bayesian Classifiers. Proceedings
of the Eleventh Conference on Uncertainty in Artificial
Intelligence. pp. 338-345. Morgan Kaufmann, San Mateo.
Valid options are:
-K
Use kernel estimation for modelling numeric attributes rather than
a single normal distribution.
- See Also:
- Serialized Form
Method Summary |
static void |
main(java.lang.String[] argv)
Main method for testing this class. |
Methods inherited from class java.lang.Object |
clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait |
NaiveBayesUpdateable
public NaiveBayesUpdateable()
main
public static void main(java.lang.String[] argv)
- Main method for testing this class.
- Parameters:
argv
- the options