代码搜索：deterministic
找到约 440 项符合「deterministic」的源代码
代码结果 440
www.eeworm.com/read/245941/12771127
m deterministic_sa.m
function [patterns, targets] = Deterministic_SA(train_patterns, train_targets, params, plot_on)
%Reduce the number of data points using the deterministic simulated annealing algorithm
%Inputs:
%
www.eeworm.com/read/245941/12771137
m deterministic_annealing.m
function [patterns, targets] = deterministic_annealing(train_patterns, train_targets, params, plot_on)
%Reduce the number of data points using the deterministic annealing algorithm
%Inputs:
% tra
www.eeworm.com/read/330850/12864753
m deterministic_boltzmann.m
function [test_targets, updates] = Deterministic_Boltzmann(train_patterns, train_targets, test_patterns, params);
% Classify using the deterministic Boltzmann algorithm
% Inputs:
% train_pattern
www.eeworm.com/read/330850/12865124
m deterministic_sa.m
function [patterns, targets] = Deterministic_SA(train_patterns, train_targets, params, plot_on)
%Reduce the number of data points using the deterministic simulated annealing algorithm
%Inputs:
%
www.eeworm.com/read/330850/12865132
m deterministic_annealing.m
function [patterns, targets] = deterministic_annealing(train_patterns, train_targets, params, plot_on)
%Reduce the number of data points using the deterministic annealing algorithm
%Inputs:
% tra
www.eeworm.com/read/317622/13500824
m deterministic_boltzmann.m
function [test_targets, updates] = Deterministic_Boltzmann(train_patterns, train_targets, test_patterns, params);
% Classify using the deterministic Boltzmann algorithm
% Inputs:
% train_pattern
www.eeworm.com/read/317622/13500945
m deterministic_sa.m
function [patterns, targets] = Deterministic_SA(train_patterns, train_targets, params, plot_on)
%Reduce the number of data points using the deterministic simulated annealing algorithm
%Inputs:
%
www.eeworm.com/read/317622/13500948
m deterministic_annealing.m
function [patterns, targets] = deterministic_annealing(train_patterns, train_targets, params, plot_on)
%Reduce the number of data points using the deterministic annealing algorithm
%Inputs:
% tra
www.eeworm.com/read/316604/13520401
m deterministic_boltzmann.m
function D = Deterministic_Boltzmann(train_features, train_targets, params, region);
% Classify using the deterministic Boltzmann algorithm
% Inputs:
% features - Train features
% targets - Tra
www.eeworm.com/read/316604/13520508
m deterministic_sa.m
function [features, targets] = Deterministic_SA(train_features, train_targets, params, region, plot_on)
%Reduce the number of data points using the deterministic simulated annealing algorithm
%Inp