代码搜索：classification
找到约 3,679 项符合「classification」的源代码
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www.eeworm.com/read/386050/8767303
m feateval.m
%FEATEVAL Evaluation of feature set for classification
%
% J = FEATEVAL(A,CRIT,T)
% J = FEATEVAL(A,CRIT,N)
%
% INPUT
% A input dataset
% CRIT string name of a method or untraine
www.eeworm.com/read/428849/8833360
m contents.m
% Statistical Pattern Recognition Toolbox (STPRtool).
% Version 2.06 18-Sep-2006
%
% Bayesian classification.
% bayescls - Bayesian classifier with reject option.
% bayesdf
www.eeworm.com/read/428849/8834991
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/282846/9056123
oilpipe_demo readme.oilpipe_demo
% Matlab code for Gaussian Processes for Classification:
% GPCLASS version 0.2 10 Nov 97
% Copyright (c) David Barber and Christopher K I Williams (1997)
% T
www.eeworm.com/read/282846/9056153
progs readme.progs
% Matlab code for Gaussian Processes for Classification:
% GPCLASS version 0.2 10 Nov 97
% Copyright (c) David Barber and Christopher K I Williams (1997)
% T
www.eeworm.com/read/282846/9056158
m minvg.m
function pvec = minvg(v)
% inverse link function, given an augmented vector
%
% Matlab code for Gaussian Processes for Classification:
% GPCLASS version 0.2 10 Nov 9
www.eeworm.com/read/183443/9158827
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/183443/9158830
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/183443/9158986
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 : @dags
www.eeworm.com/read/181389/9256458
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/