代码搜索：learner
找到约 833 项符合「learner」的源代码
代码结果 833
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/474600/6813499
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/474600/6813542
m rocchiobagging.m
function [test_targets] = RocchioBagging(train_patterns, train_targets, test_patterns, params)
% Classify using the Bagging algorithm
% Inputs:
% train_patterns - Train patterns
% train_targets
www.eeworm.com/read/474600/6813574
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/474600/6813577
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/312185/3675481
java insufficientsparsematrixcolumns.java
package jboost.learner;
class InsufficientSparseMatrixColumns extends Exception{
InsufficientSparseMatrixColumns(String message) {
this.message = message;
}
public String getMessage() {
retur
www.eeworm.com/read/418755/10928180
m demo.m
%
% DEMONSTRATION OF ADABOOST_tr and ADABOOST_te
%
% Just type "demo" to run the demo.
%
% Using adaboost with linear threshold classifier
% for a two class classification problem.
%
% Bug Reporting:
www.eeworm.com/read/467949/6997137
m demo.m
%
% DEMONSTRATION OF ADABOOST_tr and ADABOOST_te
%
% Just type "demo" to run the demo.
%
% Using adaboost with linear threshold classifier
% for a two class classification problem.
%
% Bug Reporting:
www.eeworm.com/read/439518/7706970
m demo.m
%
% DEMONSTRATION OF ADABOOST_tr and ADABOOST_te
%
% Just type "demo" to run the demo.
%
% Using adaboost with linear threshold classifier
% for a two class classification problem.
%
% Bug Reporting: