%PREX_PARZEN Parzen based denisities and classifiers
%
% PRTools example to show the differences between various ways to use the
% PARZEN procedures for estimating densities and classifiers.
help prex_parzen
delfigs
figure
echo on
delfigs
a = gendath; % two normally distributed classes, different covariances
w = a*parzenc; % Parzen classifier, single smoothing parameter optimizing
% the classification error
figure(1); scatterd(a); % show scatterplot
plotm(w); plotc(w); % show densities and classifier
title('Densities and classifier by PARZENC')
w = a*parzendc;% Parzen classifier, smoothing parameter per class
% optimizing class densities
figure(2); scatterd(a); % show scatterplot
plotm(w); plotc(w); % show densities and classifier
title('Densities and classifier by PARZENDC')
w = a*parzenm; % Parzen density, smoothing parameter per class
% optimizing class densities, combined to single density
figure(3); scatterd(a); % show scatterplot
plotm(w); plotc(w); % show density
title('Density by parzenm on labeled data')
w = +a*parzenm; % Parzen density, classes combined, so just a single
% smoothing parameter optimizing overall density
figure(4); scatterd(+a);% show scatterplot
plotm(w); % show density
title('Density by parzenm on unlabeled data')
echo off
showfigs