PARZEN_LNK(1)

NAME
parzen_lnk - Parzen Window Classifier

SYNOPSIS
Program for training and testing of a Parzen Window classifier which models the density function of each class using kernel functions centered over each training pattern.

parzen_lnk [ -per_input ] [ -per_class ] [ -minvar x ]
[ -spread x ] [ -linear ] [ -classifier_options ]

EXAMPLE
parzen_lnk -per_input -per_class -train -create \
-pathdata $LNKHOME/data/class -finput vowel.train \
-fdescribe vowel.defaults -npatterns 338 \
-fparam parzen.param

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

DESCRIPTION
Places a kernel function on each training pattern. In training, the variances of the input patterns are used to determine the kernel function variances. In testing, the class output of a pattern is the sum of the kernel function outputs for the training patterns in the class.

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

-per_input
    Kernel functions use a variance for each input dimension. The kernel function shapes are elliptical or rectangular. The default is to use a common grand variance for all dimensions which produces circular or square kernel functions.

-per_class
    Calculate kernel function variances for each class. The default is to use the same variance for all dimensions.

-minvar x
    x is the minimum variance allowed when determining kernel function shapes.

-linear
    Use rectangular pulse kernel functions. That is, for each stored training pattern, put a rectangular box around it. For any test pattern, increment the class likelihood of the pattern if it falls within the box. The box sides are placed at two standard deviations from the pattern in each input direction where the standard deviation is based on the Gaussian variance that would be used by default. If the linear flag is not set, the program uses Gaussian kernel functions with the variances set toe variance of the training data.

-spread x
    Multiply the variance terms of all kernel functions by this factor before testing.

-classifier_options
    parzen_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.
Donald Specht Probabilitic Neural Networks, in Neural Networks, Volume 3, pp 109-118, Pergamon Press, 1990.

SEE ALSO
classifier(1), parzen2c(1), parzen_feat_sel(1), parzen_plot_bound(1)

HISTORY
First written 18 April 1995 by Linda Kukolich

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