代码搜索：optimisation
找到约 403 项符合「optimisation」的源代码
代码结果 403
www.eeworm.com/read/188280/8552239
m train.m
function net = train(tutor, x, y, C, kernel, zeta, net)
% TRAIN
%
% Train a support vector classification network, using the sequential minimal
% optimisation algorithm.
%
% net = train(tut
www.eeworm.com/read/183443/9158939
m train.m
function net = train(tutor, x, y, C, kernel, zeta, net)
% TRAIN
%
% Train a support vector classification network, using the sequential minimal
% optimisation algorithm.
%
% net = train(tut
www.eeworm.com/read/181389/9256531
m train.m
function net = train(tutor, x, y, C, kernel, zeta, net)
% TRAIN
%
% Train a support vector classification network, using the sequential minimal
% optimisation algorithm.
%
% net = train(tut
www.eeworm.com/read/181388/9256678
m train.m
function net = train(tutor, x, y, C, kernel, zeta, net)
% TRAIN
%
% Train a support vector classification network, using the sequential minimal
% optimisation algorithm.
%
% net = train(tut
www.eeworm.com/read/351797/10609816
m train.m
function net = train(tutor, x, y, C, kernel, zeta, net)
% TRAIN
%
% Train a support vector classification network, using the sequential minimal
% optimisation algorithm.
%
% net = train(tut
www.eeworm.com/read/273055/10930194
m train.m
function net = train(tutor, x, y, C, kernel, zeta, net)
% TRAIN
%
% Train a support vector classification network, using the sequential minimal
% optimisation algorithm.
%
% net = train(tut
www.eeworm.com/read/469416/6976338
m demolgd1.m
%DEMOLGD1 Demonstrate simple MLP optimisation with on-line gradient descent
%
% Description
% The problem consists of one input variable X and one target variable
% T with data generated by sampli
www.eeworm.com/read/398324/7994398
m train.m
function net = train(tutor, x, y, C, kernel, zeta, net)
% TRAIN
%
% Train a support vector classification network, using the sequential minimal
% optimisation algorithm.
%
% net = train(tut
www.eeworm.com/read/398324/7994541
m train.m
function net = train(tutor, x, y, C, kernel, zeta, net)
% TRAIN
%
% Train a support vector classification network, using the sequential minimal
% optimisation algorithm.
%
% net = train(tut
www.eeworm.com/read/245176/12813287
m train.m
function net = train(tutor, x, y, C, kernel, zeta, net)
% TRAIN
%
% Train a support vector classification network, using the sequential minimal
% optimisation algorithm.
%
% net = train(tut