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/210916/15189914
m regudemo.m
%REGUDEMO Tutorial script for Regularization Tools.
% Per Christian Hansen, IMM, 12/19/97.
echo on, clf
% Part 1. The discrete Picard condition
% --------------------------------------
%
% First g
www.eeworm.com/read/471135/6898144
m regem.m
function [X, M, C, Xerr] = regem(X, options)
%REGEM Imputation of missing values with regularized EM algorithm.
%
% [X, M, C, Xerr] = REGEM(X, OPTIONS) replaces missing values
% (NaNs) in the
www.eeworm.com/read/471135/6898145
m gcvridge.m
function h_opt = gcvridge(F, d, trS0, n, r, trSmin, options)
%GCVRIDGE Finds minimum of GCV function for ridge regression.
%
% GCVRIDGE(F, d, trS0, n, r, trSmin, OPTIONS) finds the
% regularizat
www.eeworm.com/read/386050/8767371
m qdc.m
%QDC Quadratic Bayes Normal Classifier (Bayes-Normal-2)
%
% [W,R,S,M] = QDC(A,R,S,M)
% W = A*QDC([],R,S)
%
% INPUT
% A Dataset
% R,S Regularization parameters, 0
www.eeworm.com/read/161189/10439678
m contents.m
% Regularization Tools.
% Version 3.1 13-September-01.
% Copyright (c) 1993 and 1998 by Per Christian Hansen and IMM.
%
% Demonstration.
% regudemo - Tutorial introduction to Regularization T
www.eeworm.com/read/418911/10891950
m contents.m
% Regularization Tools.
% Version 4.1 9-march-08.
% Copyright (c) 1993 and 1998 by Per Christian Hansen and IMM.
%
% Demonstration.
% regudemo - Tutorial introduction to Regularization Tools.
%
%
www.eeworm.com/read/299984/7139963
m qdc.m
%QDC Quadratic Bayes Normal Classifier (Bayes-Normal-2)
%
% [W,R,S,M] = QDC(A,R,S,M)
% W = A*QDC([],R,S)
%
% INPUT
% A Dataset
% R,S Regularization parameters, 0
www.eeworm.com/read/460435/7250438
m qdc.m
%QDC Quadratic Bayes Normal Classifier (Bayes-Normal-2)
%
% [W,R,S,M] = QDC(A,R,S,M)
% W = A*QDC([],R,S)
%
% INPUT
% A Dataset
% R,S Regularization parameters, 0
www.eeworm.com/read/443605/7630284
m lda.m
function [eigvector, eigvalue, elapse] = LDA(gnd,options,data)
% LDA: Linear Discriminant Analysis
%
% [eigvector, eigvalue] = LDA(gnd, options, data)
%
% Input:
%
www.eeworm.com/read/441245/7672642
m qdc.m
%QDC Quadratic Bayes Normal Classifier (Bayes-Normal-2)
%
% [W,R,S,M] = QDC(A,R,S,M)
% W = A*QDC([],R,S)
%
% INPUT
% A Dataset
% R,S Regularization parameters, 0