prueba_qda.asv

Implementation to linear, quadratic and logistic discriminant analysis, for examples

%function prueba_QDA
clc;close all;clear all;
%generate artificial data with 4 classes and 3 variates
r = randn(3, 3, 4);
for i = 1:4
   % generate random covariance matrices for each class
   C(:,:,i) = r(:,:,i)'*r(:,:,i);
end
M = randn(4, 3)*2;       % random means
k = ceil(rand(400, 1)*4);  % random classes
X = randn(400, 3);
for i = 1:4
   X(k==i,:) = X(k==i,:)*chol(C(:,:,i)) + M(k(k==i), :);
end
f = qda(X, k); disp(f)
cov(f), plotcov(f)
plotcov(shrink(f, 1))
g = lda(X, k);
[m alpha] = mcnemar(k, f(X), g(X))