代码搜索：classification
找到约 3,679 项符合「classification」的源代码
代码结果 3,679
www.eeworm.com/read/164422/10108746
m logist2fit.m
function [beta, p] = logist2Fit(y, x, addOne, w)
% LOGIST2FIT 2 class logsitic classification
% function beta = logist2Fit(y,x, addOne)
%
% y(i) = 0/1
% x(:,i) = i'th input - we optionally append
www.eeworm.com/read/159921/10587763
m multi2dicho.m
function [Idicho]=multi2dicho(Imulti,class1)
% MULTI2DICHO decomposes multi-class problem to dichotomi.
% [Idicho]=multi2dicho(Imulti,class1)
%
% MULTI2DICHO decompose multi-class classification pr
www.eeworm.com/read/421949/10676421
m multi2dicho.m
function [Idicho]=multi2dicho(Imulti,class1)
% MULTI2DICHO decomposes multi-class problem to dichotomi.
% [Idicho]=multi2dicho(Imulti,class1)
%
% MULTI2DICHO decompose multi-class classification pr
www.eeworm.com/read/349646/10808492
m logist2fit.m
function [beta, p] = logist2Fit(y, x, addOne, w)
% LOGIST2FIT 2 class logsitic classification
% function beta = logist2Fit(y,x, addOne)
%
% y(i) = 0/1
% x(:,i) = i'th input - we optionally append
www.eeworm.com/read/349646/10809118
m logist2fit.m
function [beta, p] = logist2Fit(y, x, addOne, w)
% LOGIST2FIT 2 class logsitic classification
% function beta = logist2Fit(y,x, addOne)
%
% y(i) = 0/1
% x(:,i) = i'th input - we optionally append
www.eeworm.com/read/469416/6976106
m logist2fit.m
function [beta, p] = logist2Fit(y, x, addOne, w)
% LOGIST2FIT 2 class logsitic classification
% function beta = logist2Fit(y,x, addOne)
%
% y(i) = 0/1
% x(:,i) = i'th input - we optionally append
www.eeworm.com/read/143706/12850149
m gp_classify.m
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
www.eeworm.com/read/140851/13058406
m logist2fit.m
function [beta, p] = logist2Fit(y, x, addOne, w)
% LOGIST2FIT 2 class logsitic classification
% function beta = logist2Fit(y,x, addOne)
%
% y(i) = 0/1
% x(:,i) = i'th input - we optionally append
www.eeworm.com/read/138798/13211439
m logist2fit.m
function [beta, p] = logist2Fit(y, x, addOne, w)
% LOGIST2FIT 2 class logsitic classification
% function beta = logist2Fit(y,x, addOne)
%
% y(i) = 0/1
% x(:,i) = i'th input - we optionally append