代码搜索：selection
找到约 9,869 项符合「selection」的源代码
代码结果 9,869
www.eeworm.com/read/397099/8068812
m sequential_feature_selection.m
function [patterns, targets, pattern_numbers] = Sequential_Feature_Selection(patterns, targets, params)
% Perform sequential feature selection
%
% Inputs:
% train_patterns - Input patterns
% tr
www.eeworm.com/read/397099/8068816
m information_based_selection.m
function [patterns, targets, remaining_patterns] = Information_based_selection(patterns, targets, Npatterns)
% Koller and Sawami algorithm for pattern selection
%
% train_patterns - Input pattern
www.eeworm.com/read/397099/8068880
m feature_selection_commands.m
function feature_selection_commands(command)
%This function deals with commands generated by the feature selection module
persistent methods;
if isempty(methods)
methods = read_algorithms('
www.eeworm.com/read/397099/8068946
m exhaustive_feature_selection.m
function [patterns, targets, pattern_numbers] = Exhaustive_Feature_Selection(patterns, targets, params)
% Perform exhaustive (Brute-force) feature selection
%
% Inputs:
% train_patterns - Input
www.eeworm.com/read/245941/12770859
m sequential_feature_selection.m
function [patterns, targets, pattern_numbers] = Sequential_Feature_Selection(patterns, targets, params)
% Perform sequential feature selection
%
% Inputs:
% train_patterns - Input patterns
% tr
www.eeworm.com/read/245941/12770869
m information_based_selection.m
function [patterns, targets, remaining_patterns] = Information_based_selection(patterns, targets, Npatterns)
% Koller and Sawami algorithm for pattern selection
%
% train_patterns - Input pattern
www.eeworm.com/read/245941/12770954
m feature_selection_commands.m
function feature_selection_commands(command)
%This function deals with commands generated by the feature selection module
persistent methods;
if isempty(methods)
methods = read_algorithms('
www.eeworm.com/read/245941/12771023
m exhaustive_feature_selection.m
function [patterns, targets, pattern_numbers] = Exhaustive_Feature_Selection(patterns, targets, params)
% Perform exhaustive (Brute-force) feature selection
%
% Inputs:
% train_patterns - Input
www.eeworm.com/read/330850/12864863
m sequential_feature_selection.m
function [patterns, targets, pattern_numbers] = Sequential_Feature_Selection(patterns, targets, params)
% Perform sequential feature selection
%
% Inputs:
% train_patterns - Input patterns
% tr
www.eeworm.com/read/330850/12864871
m information_based_selection.m
function [patterns, targets, remaining_patterns] = Information_based_selection(patterns, targets, Npatterns)
% Koller and Sawami algorithm for pattern selection
%
% train_patterns - Input pattern