代码搜索：Learning
找到约 5,352 项符合「Learning」的源代码
代码结果 5,352
www.eeworm.com/read/399996/7816948
m backpropagation_cgd.m
function [test_targets, Wh, Wo, errors] = Backpropagation_CGD(train_patterns, train_targets, test_patterns, params)
% Classify using a backpropagation network with a batch learning algorithm and co
www.eeworm.com/read/399996/7816994
m backpropagation_sm.m
function [test_targets, Wh, Wo, J] = Backpropagation_SM(train_patterns, train_targets, test_patterns, params)
% Classify using a backpropagation network with stochastic learning algorithm with mome
www.eeworm.com/read/197650/7982759
m~ init_learn_param.m~
% init_learn_param.m
%
% Sets of learning parameters are defined here.
% learn_num_patch = number of patches per training image
% learn_patch_siz = size of patches (spatial dimension)
%
www.eeworm.com/read/197650/7982811
m init_learn_param.m
% init_learn_param.m
%
% Sets of learning parameters are defined here.
% learn_num_patch = number of patches per training image
% learn_patch_siz = size of patches (spatial dimension)
%
www.eeworm.com/read/196836/8055207
m contents.m
% HMMBOX, version 3.2, William Penny, Imperial College, October 1998
% Matlab toolbox for Hidden Markov Models
%
% (Adapted from Machine Learning Toolbox
% Version 1.0 01-Apr-96
% Copyright (c) by Zo
www.eeworm.com/read/397099/8068736
m backpropagation_batch.m
function [test_targets, Wh, Wo, J] = Backpropagation_Batch(train_patterns, train_targets, test_patterns, params)
% Classify using a backpropagation network with a batch learning algorithm
% Inputs
www.eeworm.com/read/397099/8068772
m backpropagation_quickprop.m
function [test_targets, Wh, Wo, J] = Backpropagation_Quickprop(train_patterns, train_targets, test_patterns, params)
% Classify using a backpropagation network with a batch learning algorithm and q
www.eeworm.com/read/397099/8068973
m backpropagation_cgd.m
function [test_targets, Wh, Wo, errors] = Backpropagation_CGD(train_patterns, train_targets, test_patterns, params)
% Classify using a backpropagation network with a batch learning algorithm and co
www.eeworm.com/read/397099/8069012
m backpropagation_sm.m
function [test_targets, Wh, Wo, J] = Backpropagation_SM(train_patterns, train_targets, test_patterns, params)
% Classify using a backpropagation network with stochastic learning algorithm with mome
www.eeworm.com/read/245941/12770746
m backpropagation_batch.m
function [test_targets, Wh, Wo, J] = Backpropagation_Batch(train_patterns, train_targets, test_patterns, params)
% Classify using a backpropagation network with a batch learning algorithm
% Inputs