代码搜索：Regularization
找到约 355 项符合「Regularization」的源代码
代码结果 355
www.eeworm.com/read/400577/11572698
m nusvo.m
%NUSVO Support Vector Optimizer: NU algorithm
%
% [V,J,NU,C] = NUSVO(K,NLAB,NU,OPTIONS)
%
% INPUT
% K Similarity matrix
% NLAB Label list consisting of -1/+1
% NU Regularization parame
www.eeworm.com/read/471135/6898151
m pttls.m
function [Xr, Sr, rho, eta] = pttls(V, d, colA, colB, r)
%PTTLS Truncated TLS regularization with permuted columns.
%
% Given matrices A and B, the total least squares (TLS) problem
% consists o
www.eeworm.com/read/386050/8767606
m svo_nu.m
%SVO_NU Support Vector Optimizer: NU algorithm
%
% [V,J,C] = SVO(K,NLAB,NU,PD)
%
% INPUT
% K Similarity matrix
% NLAB Label list consisting of -1/+1
% NU Regularization parameter (0 <
www.eeworm.com/read/161189/10439694
m cgsvd.m
function [U,sm,X,V] = cgsvd(A,L)
%CGSVD Compact generalized SVD of a matrix pair in regularization problems.
%
% sm = cgsvd(A,L)
% [U,sm,X,V] = cgsvd(A,L) , sm = [sigma,mu]
%
% Computes the generaliz
www.eeworm.com/read/299984/7140053
m svo_nu.m
%SVO_NU Support Vector Optimizer: NU algorithm
%
% [V,J,C] = SVO(K,NLAB,NU,PD)
%
% INPUT
% K Similarity matrix
% NLAB Label list consisting of -1/+1
% NU Regularization parameter (0 <
www.eeworm.com/read/460435/7250528
m svo_nu.m
%SVO_NU Support Vector Optimizer: NU algorithm
%
% [V,J,C] = SVO(K,NLAB,NU,PD)
%
% INPUT
% K Similarity matrix
% NLAB Label list consisting of -1/+1
% NU Regularization parameter (0 <
www.eeworm.com/read/450608/7480156
m svo_nu.m
%SVO_NU Support Vector Optimizer: NU algorithm
%
% [V,J,C] = SVO(K,NLAB,NU,PD)
%
% INPUT
% K Similarity matrix
% NLAB Label list consisting of -1/+1
% NU Regularization parameter (0 <
www.eeworm.com/read/441245/7672738
m svo_nu.m
%SVO_NU Support Vector Optimizer: NU algorithm
%
% [V,J,C] = SVO(K,NLAB,NU,PD)
%
% INPUT
% K Similarity matrix
% NLAB Label list consisting of -1/+1
% NU Regularization parameter (0 <
www.eeworm.com/read/137160/13341950
m svo_nu.m
%SVO_NU Support Vector Optimizer: NU algorithm
%
% [V,J,C] = SVO(K,NLAB,NU,PD)
%
% INPUT
% K Similarity matrix
% NLAB Label list consisting of -1/+1
% NU Regularization parameter (0 <
www.eeworm.com/read/314653/13562284
m svo_nu.m
%SVO_NU Support Vector Optimizer: NU algorithm
%
% [V,J,C] = SVO(K,NLAB,NU,PD)
%
% INPUT
% K Similarity matrix
% NLAB Label list consisting of -1/+1
% NU Regularization parameter (0 <