代码搜索：Patterns
找到约 8,017 项符合「Patterns」的源代码
代码结果 8,017
www.eeworm.com/read/399996/7817099
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/397099/8068970
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/397099/8069075
m pocket.m
function [test_targets, w_pocket] = Pocket(train_patterns, train_targets, test_patterns, alg_param)
% Classify using the pocket algorithm (an improvement on the perceptron)
% Inputs:
% train_pat
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/245941/12771216
m pocket.m
function [test_targets, w_pocket] = Pocket(train_patterns, train_targets, test_patterns, alg_param)
% Classify using the pocket algorithm (an improvement on the perceptron)
% Inputs:
% train_pat
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/330850/12865051
m lms.m
function [test_targets, a, updates] = LMS(train_patterns, train_targets, test_patterns, params)
% Classify using the least means square algorithm
% Inputs:
% train_patterns - Train patterns
% t
www.eeworm.com/read/330850/12865196
m pocket.m
function [test_targets, w_pocket] = Pocket(train_patterns, train_targets, test_patterns, alg_param)
% Classify using the pocket algorithm (an improvement on the perceptron)
% Inputs:
% train_pat
www.eeworm.com/read/317622/13500918
m lms.m
function [test_targets, a, updates] = LMS(train_patterns, train_targets, test_patterns, params)
% Classify using the least means square algorithm
% Inputs:
% train_patterns - Train patterns
% t
www.eeworm.com/read/317622/13500965
m pocket.m
function [test_targets, w_pocket] = Pocket(train_patterns, train_targets, test_patterns, alg_param)
% Classify using the pocket algorithm (an improvement on the perceptron)
% Inputs:
% train_pat