代码搜索：Multivariate Analysis
找到约 10,000 项符合「Multivariate Analysis」的源代码
代码结果 10,000
www.eeworm.com/read/317622/13500820
m multivariate_splines.m
function test_targets = Multivariate_Splines(train_patterns, train_targets, test_patterns, params)
% Classify using multivariate adaptive regression splines
% Inputs:
% train_patterns - Train pa
www.eeworm.com/read/316604/13520397
m multivariate_splines.m
function D = Multivariate_Splines(train_features, train_targets, params, region)
% Classify using multivariate adaptive regression splines
% Inputs:
% features - Train features
% targets -
www.eeworm.com/read/359185/6352488
m multivariate_splines.m
function D = Multivariate_Splines(train_features, train_targets, params, region)
% Classify using multivariate adaptive regression splines
% Inputs:
% features - Train features
% targets -
www.eeworm.com/read/493206/6398466
m multivariate_splines.m
function D = Multivariate_Splines(train_features, train_targets, params, region)
% Classify using multivariate adaptive regression splines
% Inputs:
% features - Train features
% targets -
www.eeworm.com/read/410924/11264779
m multivariate_splines.m
function D = Multivariate_Splines(train_features, train_targets, params, region)
% Classify using multivariate adaptive regression splines
% Inputs:
% features - Train features
% targets -
www.eeworm.com/read/405069/11472168
m multivariate_splines.m
function test_targets = Multivariate_Splines(train_patterns, train_targets, test_patterns, params)
% Classify using multivariate adaptive regression splines
% Inputs:
% train_patterns - Train pa
www.eeworm.com/read/250980/12372069
m multivariate_gauss.m
function s= multivariate_gauss(x,P,n)
%function s= multivariate_gauss(x,P,n)
%
% INPUTS:
% (x, P) mean vector and covariance matrix
% obtain n samples
% OUTPUT:
% sample set
%
% Random
www.eeworm.com/read/131588/14136165
m multivariate_splines.m
function D = Multivariate_Splines(train_features, train_targets, params, region)
% Classify using multivariate adaptive regression splines
% Inputs:
% features - Train features
% targets -
www.eeworm.com/read/129915/14217607
m multivariate_splines.m
function D = Multivariate_Splines(train_features, train_targets, params, region)
% Classify using multivariate adaptive regression splines
% Inputs:
% features - Train features
% targets -
www.eeworm.com/read/216806/14991728
m multivariate_gauss.m
function s= multivariate_gauss(x,P,n)
%function s= multivariate_gauss(x,P,n)
%
% INPUTS:
% (x, P) mean vector and covariance matrix
% obtain n samples
% OUTPUT:
% sample set
%
% Random sample f