GAUSS_LNK(1)

NAME
gauss_lnk - Gaussian Classifier

SYNOPSIS
Program for training and testing of a Gaussian classifier which models each class with a single unimodal Gaussian distribution.

gauss_lnk [ -full ] [ -per_class ] [ -minvar x ]
[ -max_ratio x ] [ -classifier_options ]

EXAMPLE
gauss_lnk -full -per_class -train -create -pathdata $LNKHOME/data/class \
-finput vowel.train -fdescribe vowel.defaults \
-npatterns 338 -fparam gauss.param

gauss_lnk -pathdata $LNKHOME/data/class -finput vowel.eval \
-fdescribe vowel.defaults -npatterns 166 -fparam gauss.param

DESCRIPTION
Finds the mean of each class in the input data. Finds a covariance matrix for each class or finds one for all of the data and uses it for all of the classes. The covariance matrix or matrices can be full or diagonal.

OPTIONS
-- Prints a list of all flags and arguments.

-full
    Calculate full covariance matrices, rather than diagonal.

-per_class
    Calculate a covariance matrix for each class. The default is to use a single grand covariance matrix for all classes.

-minvar x
    x is the minimum value for on diagonal entries of the covariance matrices stored during training.

-max_ratio x
    x is the maximum allowable ratio of the largest eigenvalue to each of the others when doing a singular-value-decomposition matrix inversion.

-classifier_options
    gauss_lnk accepts the general classifier arguments described on the classifier(1) manual page.

    Notes about argments from general list:

    -random
        This flag has an effect only when adjust_train_priors is set.

REFERENCE
Richard O. Duda and Peter E. Hart, Pattern Classification and Scene Analysis, John Wiley & Sons, New York, 1973. Pages 24-31.

SEE ALSO
classifier(1), gauss2c(1), gauss_feat_sel(1), plot_gauss(1), gauss_plot_bound(1)

HISTORY
First written 26 May 1992 by Linda Kukolich

BUGS
Send bug reports to Linda Kukolich (kukolich@sst.ll.mit.edu)