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/316604/13520512
m deterministic_annealing.m
function [features, targets] = deterministic_annealing(train_features, train_targets, params, region, plot_on)
%Reduce the number of data points using the deterministic annealing algorithm
%Inputs
www.eeworm.com/read/140847/5779254
m deterministic_cpd.m
function CPD = deterministic_CPD(bnet, self, fname, pfail)
% DETERMINISTIC_CPD Make a tabular CPD representing a (noisy) deterministic function
%
% CPD = deterministic_CPD(bnet, self, fname)
% This ca
www.eeworm.com/read/133943/5897438
m deterministic_cpd.m
function CPD = deterministic_CPD(bnet, self, fname, pfail)
% DETERMINISTIC_CPD Make a tabular CPD representing a (noisy) deterministic function
%
% CPD = deterministic_CPD(bnet, self, fname)
% This ca
www.eeworm.com/read/359185/6352492
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/359185/6352575
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
www.eeworm.com/read/359185/6352579
m deterministic_annealing.m
function [features, targets] = deterministic_annealing(train_features, train_targets, params, region, plot_on)
%Reduce the number of data points using the deterministic annealing algorithm
%Inputs
www.eeworm.com/read/493206/6398470
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/493206/6398585
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
www.eeworm.com/read/493206/6398589
m deterministic_annealing.m
function [features, targets] = deterministic_annealing(train_features, train_targets, params, region, plot_on)
%Reduce the number of data points using the deterministic annealing algorithm
%Inputs
www.eeworm.com/read/410924/11264786
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