MATLAB File Help: dml.naive

  naive gaussian naive Bayes classifier.
 
    DESCRIPTION
    Estimates discrete priors and class-conditional gaussian distributions 
    for the individual parameters.
 
    Suitable for online learning (repeated calls to the train function).
    Note: sometimes we get complex values for sigma; to-be-solved; caused by
    instability of the online algorithm
 
    REFERENCE
    Updating formulae and a pairwise algorithm for computing sample
    variances by Tony F. Chan Gene H. Golub Randall J. LeVeque
 
    EXAMPLE
    X = rand(10,20); Y = [1 1 1 1 1 2 2 2 2 2]';
    m = dml.naive
    m = m.train(X,Y);
    Z = m.test(X);
 
    DEVELOPER
    Marcel van Gerven (m.vangerven@donders.ru.nl)

Superclasses	dml.method
Sealed	false
Construct on load	false

S	sum per class
SS	sum of squares per class
indims	dimensions of the input data (excluding the trial dim and time dim in time series data)
n	number of samples per class and feature
restart	when false, starts at the previously learned parameters; needed for online learning and grid search
verbose	whether or not to generate diagnostic output

	model	returns
	test
	train	handle multiple datasets