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/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/317622/13500906
m leader_follower.m
function [patterns, targets, label, W] = Leader_Follower(train_patterns, train_targets, params, plot_on)
%Reduce the number of data points using the basic leader-follower clustering algorithm
%Inp
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/405069/11472254
m leader_follower.m
function [patterns, targets, label, W] = Leader_Follower(train_patterns, train_targets, params, plot_on)
%Reduce the number of data points using the basic leader-follower clustering algorithm
%Inp
www.eeworm.com/read/405069/11472293
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/474600/6813509
m leader_follower.m
function [patterns, targets, label, W] = Leader_Follower(train_patterns, train_targets, params, plot_on)
%Reduce the number of data points using the basic leader-follower clustering algorithm
%Inp
www.eeworm.com/read/474600/6813550
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/389964/8490758
htm readme.htm
Stock Prediction Based on Price Patterns 1.0
Stock Prediction Based on Price Patterns 1.0 - Matlab source code
www.eeworm.com/read/179335/9360798
readme
This directory contains 4 test files. They test itemset, sequence, tree and graph mining.
For sequence test, two variation exists (embedded, induced) and for tree, four variations
exists(ordered/unord
www.eeworm.com/read/425005/10388411
me read.me
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Back Propagation Neural Net Engine v1.32u
for C programmers