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/283021/9046853
txt 新建 文本文档 (4).txt
function D = C4_5(train_features, train_targets, inc_node, region)
% Classify using Quinlan′s C4.5 algorithm
% Inputs:
% features - Train features
% targets - Train targets
% inc_node -
www.eeworm.com/read/376518/9315901
m c4_5.m
function D = C4_5(train_features, train_targets, inc_node, region)
% Classify using Quinlan's C4.5 algorithm
% Inputs:
% features - Train features
% targets - Train targets
% inc_node -
www.eeworm.com/read/177129/9468775
m c4_5.m
function D = C4_5(train_features, train_targets, inc_node, region)
% Classify using Quinlan's C4.5 algorithm
% Inputs:
% features - Train features
% targets - Train targets
% inc_node -
www.eeworm.com/read/372113/9521319
m ho_kashyap.m
function [test_targets, w_percept, b] = Ho_Kashyap(train_patterns, train_targets, test_patterns, params)
% Classify using the using the Ho-Kashyap algorithm
% Inputs:
% train_patterns - Train pa
www.eeworm.com/read/362008/10023989
m ho_kashyap.m
function [test_targets, w_percept, b] = Ho_Kashyap(train_patterns, train_targets, test_patterns, params)
% Classify using the using the Ho-Kashyap algorithm
% Inputs:
% train_patterns - Train pa
www.eeworm.com/read/357874/10199177
m ho_kashyap.m
function [test_targets, w_percept, b] = Ho_Kashyap(train_patterns, train_targets, test_patterns, params)
% Classify using the using the Ho-Kashyap algorithm
% Inputs:
% train_patterns - Train pa
www.eeworm.com/read/349842/10796672
m c4_5.m
function D = C4_5(train_features, train_targets, inc_node, region)
% Classify using Quinlan's C4.5 algorithm
% Inputs:
% features - Train features
% targets - Train targets
% inc_node -
www.eeworm.com/read/440440/7689357
m ho_kashyap.m
function [test_targets, w_percept, b] = Ho_Kashyap(train_patterns, train_targets, test_patterns, params)
% Classify using the using the Ho-Kashyap algorithm
% Inputs:
% train_patterns - Train pa
www.eeworm.com/read/436138/7776207
m c4_5.m
function D = C4_5(train_features, train_targets, inc_node, region)
% Classify using Quinlan's C4.5 algorithm
% Inputs:
% features - Train features
% targets - Train targets
% inc_node -
www.eeworm.com/read/399996/7816989
m ho_kashyap.m
function [test_targets, w_percept, b] = Ho_Kashyap(train_patterns, train_targets, test_patterns, params)
% Classify using the using the Ho-Kashyap algorithm
% Inputs:
% train_patterns - Train pa