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/181389/9256462
m strip.m
function net = strip(net, tolerance)
% STRIP
%
% Delete support vectors from a support vector classification network for which
% the magnitude of the corresponding weight is less than a given to
www.eeworm.com/read/181388/9256590
m getnsv.m
function nsv = getnsv(net)
% GETNSV
%
% Accessor method returning the number of support vectors of a support vector
% classification network.
%
% n = getnsv(net);
%
% File : @svc/
www.eeworm.com/read/181388/9256594
m strip.m
function net = strip(net, tolerance)
% STRIP
%
% Delete support vectors from a support vector classification network for which
% the magnitude of the corresponding weight is less than a given to
www.eeworm.com/read/362246/10009287
m contents.m
% Statistical Pattern Recognition Toolbox (STPRtool).
% Version 2.05 19-Oct-2005
%
% Bayesian classification.
% bayescls - Bayesian classifier with reject option.
% bayesdf
www.eeworm.com/read/362246/10010505
m~ contents.m~
% Statistical Pattern Recognition Toolbox (STPRtool).
% Version 2.04 22-Dec-2004
%
% Bayesian classification.
% bayescls - Bayesian classifier with reject option.
% bayesdf
www.eeworm.com/read/280595/10310579
m contents.m
% Statistical Pattern Recognition Toolbox (STPRtool).
% Version 2.04 22-Dec-2004
%
% Bayesian classification.
% bayescls - Bayesian classifier with reject option.
% bayesdf
www.eeworm.com/read/280595/10312472
m~ contents.m~
% Statistical Pattern Recognition Toolbox (STPRtool).
% Version 2.03 14-Dec-2004
%
% Bayesian classification.
% bayescls - Bayesian classifier with reject option.
% bayesdf
www.eeworm.com/read/425546/10349213
m demtrain.m
function demtrain(action);
%DEMTRAIN Demonstrate training of MLP network.
%
% Description
% DEMTRAIN brings up a simple GUI to show the training of an MLP
% network on classification and regressi
www.eeworm.com/read/351797/10609655
m getnsv.m
function nsv = getnsv(net)
% GETNSV
%
% Accessor method returning the number of support vectors of a support vector
% classification network.
%
% n = getnsv(net);
%
% File : @svc/
www.eeworm.com/read/351797/10609664
m strip.m
function net = strip(net, tolerance)
% STRIP
%
% Delete support vectors from a support vector classification network for which
% the magnitude of the corresponding weight is less than a given to