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/341972/12052315
m rbf_network.m
function [test_targets, mu, Wo] = RBF_Network(train_patterns, train_targets, test_patterns, Nh)
% Classify using a radial basis function network algorithm
% Inputs:
% train_patterns - Train patt
www.eeworm.com/read/474600/6813404
m parzen.m
function test_targets = parzen(train_patterns, train_targets, test_patterns, hn)
% Classify using the Parzen windows algorithm
% Inputs:
% train_patterns - Train patterns
% train_targets - Trai
www.eeworm.com/read/474600/6813462
m projection_pursuit.m
function [test_targets, V, Wo] = Projection_Pursuit(train_patterns, train_targets, test_patterns, Ncomponents)
% Classify using projection pursuit regression
% Inputs:
% train_patterns - Train p
www.eeworm.com/read/474600/6813558
m rbf_network.m
function [test_targets, mu, Wo] = RBF_Network(train_patterns, train_targets, test_patterns, Nh)
% Classify using a backpropagation network with a batch learning algorithm
% Inputs:
% train_patte
www.eeworm.com/read/474600/6813573
asv parzen.asv
function test_targets = parzen(train_patterns, train_targets, test_patterns, hn)
% Classify using the Parzen windows algorithm
% Inputs:
% train_patterns - Train patterns
% train_targets - Trai
www.eeworm.com/read/286662/8751767
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/286662/8752027
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/372113/9521158
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/372113/9521387
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/362008/10023852
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