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/256398/12001745
m exlar1.m
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Multiple Kernel Estimation using the KBP
% the plotting describes the regularization path
%
%
% Paper :
% V. Gui
www.eeworm.com/read/342008/12047284
m ldc.m
%LDC Linear Discriminant Classifier
%
% W = ldc(A,r,s)
%
% Computation of a linear discriminant between the classes of the
% dataset A assuming normal densities with equal covariance
% matrices.
www.eeworm.com/read/338293/12314541
m l_curve.m
function [reg_corner,rho,eta,reg_param] = l_curve(U,sm,b,method,L,V)
%L_CURVE Plot the L-curve and find its "corner".
%
% [reg_corner,rho,eta,reg_param] =
% l_curve(U,s,b,method)
%
www.eeworm.com/read/295595/8150731
m exlar1.m
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Multiple Kernel Estimation using the KBP
% the plotting describes the regularization path
%
%
% Paper :
% V. Gui
www.eeworm.com/read/393865/8257751
m exlar1.m
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Multiple Kernel Estimation using the KBP
% the plotting describes the regularization path
%
%
% Paper :
% V. Gui
www.eeworm.com/read/293183/8310646
m ldc.m
%LDC Linear Discriminant Classifier
%
% W = ldc(A,r,s)
%
% Computation of a linear discriminant between the classes of the
% dataset A assuming normal densities with equal covariance
% matrices.
www.eeworm.com/read/411401/11246858
m makeregmatrixface.m
function R=MakeRegmatrixFace(Element);
% Function R=MakeRegmatrixFace(Element);
% computes a regularization matrix R which is a
% version of 2D difference.
%
% INPUT
%
% Element = element structure
www.eeworm.com/read/191566/8428212
m bookstein.m
function [cx,cy,E,L]=bookstein(X,Y,beta_k);
% [cx,cy,E,L]=bookstein(X,Y,beta_k);
%
% Bookstein PAMI89
N=size(X,1);
Nb=size(Y,1);
if N~=Nb
error('number of landmarks must be equal')
end
www.eeworm.com/read/289488/8548398
m exclassrn.m
%
% Example of Checker Data
% classification with regularization networks
%
%
clear all
close all
%-------------------------------------------------------------------
%
www.eeworm.com/read/289321/8559359
m gcvfctn.m
function g = gcvfctn(h, d, fc2, trS0, dof0)
%GCVFCTN Evaluate object function for generalized cross-validation.
%
% GCVFCTN(h, d, fc2, trS0, dof0) returns the function values of the
% generaliz