代码搜索：Classify
找到约 2,639 项符合「Classify」的源代码
代码结果 2,639
www.eeworm.com/read/245941/12770866
m relaxation_bm.m
function [test_targets, a] = Relaxation_BM(train_patterns, train_targets, test_patterns, params)
% Classify using the batch relaxation with margin algorithm
% Inputs:
% train_patterns - Train pa
www.eeworm.com/read/245941/12770986
asv bagging.asv
function [test_targets] = Bagging(train_patterns, train_targets, test_patterns, params)
% Classify using the Bagging algorithm
% Inputs:
% train_patterns - Train patterns
% train_targets - Trai
www.eeworm.com/read/245941/12771018
m locboost.m
function [test_targets, P, theta, phi] = LocBoost(train_patterns, train_targets, test_patterns, params)
% Classify using the local boosting algorithm
% Inputs:
% train_patterns - Train patterns
www.eeworm.com/read/245941/12771057
m lms.m
function [test_targets, updates] = LMS(train_patterns, train_targets, test_patterns, params)
% Classify using the least means square algorithm
% Inputs:
% train_patterns - Train patterns
% trai
www.eeworm.com/read/245941/12771144
m genetic_algorithm.m
function test_targets = Genetic_Algorithm(train_patterns, train_targets, test_patterns, params)
% Classify using a basic genetic algorithm
% Inputs:
% training_patterns - Train patterns
% tra
www.eeworm.com/read/245941/12771215
m bagging.m
function [test_targets] = Bagging(train_patterns, train_targets, test_patterns, params)
% Classify using the Bagging algorithm
% Inputs:
% train_patterns - Train patterns
% train_targets - Trai
www.eeworm.com/read/245941/12771220
m basebagging.m
function test_targets = BaseBagging(train_patterns, train_targets, test_patterns, params)
% Classify using the Bagging algorithm
% Inputs:
% train_patterns - Train patterns
% train_targets - Tr
www.eeworm.com/read/245941/12771222
m relaxation_ssm.m
function [test_targets, a] = Relaxation_SSM(train_patterns, train_targets, test_patterns, params)
% Classify using the single-sample relaxation with margin algorithm
% Inputs:
% train_patterns -
www.eeworm.com/read/330850/12864719
m cascade_correlation.m
function [test_targets, Wh, Wo, J] = Cascade_Correlation(train_patterns, train_targets, test_patterns, params)
% Classify using a backpropagation network with the cascade-correlation algorithm
% I
www.eeworm.com/read/330850/12864742
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