com.imsl.test.example.datamining

Class NaiveBayesClassifierEx3

java.lang.Object

com.imsl.test.example.datamining.NaiveBayesClassifierEx3

public class NaiveBayesClassifierEx3
extends Object

Trains a classifier with a user supplied probability function.

This example is similar to NaiveBayesClassifierEx1, where we train a classifier on Fisher's Iris data using 140 of the 150 continuous patterns, and then classify ten remaining plants using their sepal and petal measurements.

Instead of using the NormalDistribution class, a user supplied normal (Gaussian) distribution is supplied directly. Rather than calculating the means and standard deviations from the data, as is done by the NormalDistribution's eval(double[]) method, the user supplied class requires the means and standard deviations in the class constructor. The output is the same as in NaiveBayesClassifierEx1, since the means and standard deviations in this example are simply rounded means and standard deviations of the actual data subset by target classifications.

See Also:

Example, Output

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	NaiveBayesClassifierEx3.TestGaussFcn1 Defines the user supplied probability distribution.

Constructor Summary

Constructors

Constructor and Description
NaiveBayesClassifierEx3()

Method Summary

Modifier and Type	Method and Description
static void	main(String[] args) The main method for the example.

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

NaiveBayesClassifierEx3

public NaiveBayesClassifierEx3()

Method Detail

main

public static void main(String[] args)
                 throws Exception

The main method for the example.

Throws:

Exception