代码搜索：classifier
找到约 4,824 项符合「classifier」的源代码
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www.eeworm.com/read/393436/8287391
txt read_me.txt
The following files provide a Matlab based demonstration of the
GP classifier for multiple classes as detailed in the paper
Girolami, M., Rogers, S.,
Variational Bayesian Multinomial Probit Regr
www.eeworm.com/read/293183/8310142
m invsigm.m
%INVSIGM Inverse sigmoid map
%
% W = W*invsigm
% B = invsigm(A)
%
% Inverse sigmoidal transformation from classifier to map, transforming
% posterior probabilities into distances.
%
% See also da
www.eeworm.com/read/293183/8310624
m cleval.m
%CLEVAL Classifier evaluation (learning curve)
%
% [e,s] = cleval(classf,A,learnsizes,n,T,print)
%
% Generates at random for all class sizes of the training set
% defined in the vector 'learnsizes
www.eeworm.com/read/293183/8310629
m clevalb.m
%CLEVAL Classifier evaluation (learning curve), bootstrap version
%
% [e,s] = cleval(classf,A,learnsizes,n,T,print)
%
% Generates at random for all class sizes of the training set
% defined in the
www.eeworm.com/read/293183/8310632
m subsc.m
%SUBSC Subspace Classifier
%
% W = subsc(A,n)
%
% n-dimensional subspace maps are computed for each class of the dataset A
% using PCA, such that they contain the origin. All object in A are normalize
www.eeworm.com/read/411674/11233879
m train_ocr.m
% TRAIN_OCR Training of OCR classifier based on multiclass SVM.
%
% Description:
% The following steps are performed:
% - Training set is created from data in directory ExamplesDir.
% - Mult
www.eeworm.com/read/289680/8534974
m getsv.m
function sv = getsv(net)
% GETSV
%
% Accessor method returning the support vectors of a support vector
% classifier network.
%
% sv = getsv(net);
%
% File : @svc/getsv.m
%
% D
www.eeworm.com/read/289680/8534985
m getw.m
function w = getw(net)
% GETW
%
% Accessor method returning the weights of a support vector classifier network.
%
% w = getw(net);
%
% File : @svc/getw.m
%
% Date : Tuesd
www.eeworm.com/read/188280/8552108
m getsv.m
function sv = getsv(net)
% GETSV
%
% Accessor method returning the support vectors of a support vector
% classifier network.
%
% sv = getsv(net);
%
% File : @svc/getsv.m
%
% D
www.eeworm.com/read/188280/8552123
m getw.m
function w = getw(net)
% GETW
%
% Accessor method returning the weights of a support vector classifier network.
%
% w = getw(net);
%
% File : @svc/getw.m
%
% Date : Tuesd