MATLAB File Help: cv.NormalBayesClassifier

cv.NormalBayesClassifier

Bayes classifier for normally distributed data

Normal Bayes Classifier

This simple classification model assumes that feature vectors from each class are normally distributed (though, not necessarily independently distributed). So, the whole data distribution function is assumed to be a Gaussian mixture, one component per class. Using the training data the algorithm estimates mean vectors and covariance matrices for every class, and then it uses them for prediction.

References

[Fukunaga90]:

K. Fukunaga. "Introduction to Statistical Pattern Recognition", 2e. New York: Academic Press, 1990.

Class Details

Superclasses	handle
Sealed	false
Construct on load	false

Constructor Summary

NormalBayesClassifier

Creates/trains a new Bayes classifier model

Property Summary

Object ID

Method Summary

	addlistener	Add listener for event.
	calcError	Computes error on the training or test dataset
	clear	Clears the algorithm state
	delete	Destructor
	empty	Returns true if the algorithm is empty
	eq	== (EQ) Test handle equality.
	findobj	Find objects matching specified conditions.
	findprop	Find property of MATLAB handle object.
	ge	>= (GE) Greater than or equal relation for handles.
	getDefaultName	Returns the algorithm string identifier
	getVarCount	Returns the number of variables in training samples
	gt	> (GT) Greater than relation for handles.
	isClassifier	Returns true if the model is a classifier
	isTrained	Returns true if the model is trained
Sealed	isvalid	Test handle validity.
	le	<= (LE) Less than or equal relation for handles.
	load	Loads algorithm from a file or a string
	lt	< (LT) Less than relation for handles.
	ne	~= (NE) Not equal relation for handles.
	notify	Notify listeners of event.
	predict	Predicts responses for input samples
	predictProb	Predicts the response for sample(s)
	save	Saves the algorithm parameters to a file or a string
	train	Trains the statistical model