代码搜索：svc
找到约 5,868 项符合「svc」的源代码
代码结果 5,868
www.eeworm.com/read/289710/8533766
m svc.m
function [nsv, alpha, b0] = svc(X,Y,ker,C)
%SVC Support Vector Classification
%
% Usage: [nsv alpha bias] = svc(X,Y,ker,C)
%
% Parameters: X - Training inputs
% Y - Training t
www.eeworm.com/read/289680/8534967
m svc.m
function net = svc(arg, sv, w, bias)
% SVC
%
% Construct a support vector classification (SVC) network object.
%
% Examples:
%
% % default constructor (linear, hardmargin SVC with no suppo
www.eeworm.com/read/389274/8536664
m svc.m
function net = svc(arg, sv, w, bias)
%
if nargin == 0
% this is the default constructor
net.kernel = linear;
net.sv = [];
net.w = [];
net.bias = 0;
www.eeworm.com/read/188280/8552099
m svc.m
function net = svc(arg, sv, w, bias)
% SVC
%
% Construct a support vector classification (SVC) network object.
%
% Examples:
%
% % default constructor (linear, hardmargin SVC with no suppo
www.eeworm.com/read/289416/8552749
m svc.m
function [nsv, alpha, b0] = svc(X,Y,ker,C)
%SVC Support Vector Classification
%
% Usage: [nsv alpha bias] = svc(X,Y,ker,C)
%
% Parameters: X - Training inputs
% Y - Training t
www.eeworm.com/read/431675/8661774
m svc.m
%SVC Support Vector Classifier
%
% [W,J] = svc(A,type,par,C)
%
% Optimizes a support vector classifier for the dataset A by
% quadratic programming. The classifier can be of one of the types
% as
www.eeworm.com/read/386050/8767469
m svc.m
%SVC Support Vector Classifier
%
% [W,J] = SVC(A,KERNEL,C)
% [W,J] = SVC(A,TYPE,PAR,C)
% W = A*SVC([],KERNEL,C)
% W = A*SVC([],TYPE,PAR,C)
%
% INPUT
% A Dataset
% KERNEL - Un
www.eeworm.com/read/384922/8833956
m svc.m
function [nsv, alpha, b0] = svc(X,Y,ker,C)
%SVC Support Vector Classification
%
% Usage: [nsv alpha bias] = svc(X,Y,ker,C)
%
% Parameters: X - Training inputs
% Y - Training t
www.eeworm.com/read/384903/8834882
m svc.m
function [nsv, alpha, b0] = svc(X,Y,ker,C)
%SVC Support Vector Classification
%
% Usage: [nsv alpha bias] = svc(X,Y,ker,C)
%
% Parameters: X - Training inputs
% Y - Training t
www.eeworm.com/read/284759/8900417
m svc.m
function [nsv, alpha, b0] = svc(X,Y,ker,C)
%SVC Support Vector Classification
%
% Usage: [nsv alpha bias] = svc(X,Y,ker,C)
%
% Parameters: X - Training inputs
% Y - Training t