gp_classify.m

一个matlab的工具包,里面包括一些分类器 例如 KNN KMEAN SVM NETLAB 等等有很多.

function  [Y_compute, Y_prob] = GP_classify(para, X_train, Y_train, X_test, Y_test, num_class)
% Gaussian Process for Classification/Regression
% Not Ready yet

global temp_model_file;
[class_set, num_class] = GetClassSet(Y_train);

if (nargin <= 5)
    num_class = 2;
end;

p = str2num(char(ParseParameter(para, {'-PriorMean'; '-PriorVariance'}, {'0'; '1'})));
pr_mean = p(1);
pr_variance = p(2);
num_feature = size(X_train, 2);

% Fix seeds for reproducible results
rand('state', 42);

for i = 1:num_class    
    % Convert the binary labels into +/-1
    data =  X_train(Y_train == class_set(i),:);
    
    % Now train to find the hyperparameters.
    options = foptions;
    options(1) = 1;    % Display training error values
    options(14) = 20;
    
    prior.pr_mean = pr_mean;
    prior.pr_var = pr_variance;
    net = gp(1, 'ratquad'); 
    % net = gp(1, 'sqexp'); 
    net = gpinit(net, data, Y_train, prior);
    [net, options] = netopt(net, options, data, Y_train, 'scg');
    
    cn = gpcovar(net, data); 
    cninv = inv(cn);
    [ytest, sigsq] = gpfwd(net, X_test, cninv);
    sig = sqrt(sigsq);    
end;

[Y_prob Index] = max(Y_prob_matrix, [], 2);
Y_compute = class_set(Index);