代码搜索：Best 开发教程
找到约 10,000 项符合「Best 开发教程」的源代码
代码结果 10,000
www.eeworm.com/read/298649/7946922
c select.c
/*
* GENESIS Copyright (c) 1986, 1990 by John J. Grefenstette
* This program may be freely copied for educational
* and research purposes. All other rights reserved.
*
* file: select
www.eeworm.com/read/298649/7947393
m select6.m
function [out,coefs,pin,best,bestpin]=select6(chrom,d,x,y,s1,s2,s3,best,bestpin)
%
% out=select(in);
%
% selects a new population
%
%
%
% Mix up the population
%
chrom=shuffle(chrom);
%
www.eeworm.com/read/397122/8065763
m trimmedmse.m
function [cost,retained] = trimmedmse(R,beta,V);
% Calculate trimmed mean of the squared value of the residuals.
%
% cost = trimmedmse(R);
%
% The factor where one trimms off the normed residuals is
www.eeworm.com/read/397099/8069032
m genetic_culling.m
function [patterns, targets, pattern_numbers] = genetic_culling(patterns, targets, params)
% Culling type genetic algorithm for feature selection
%
% Inputs:
% train_patterns - Input patterns
%
www.eeworm.com/read/245941/12771134
m genetic_culling.m
function [patterns, targets, pattern_numbers] = genetic_culling(patterns, targets, params)
% Culling type genetic algorithm for feature selection
%
% Inputs:
% train_patterns - Input patterns
%
www.eeworm.com/read/245261/12807759
out art002.out
BEST NEURON:0
IN: 1 1 1 1 0 0 1 0 0 1 0 0 1 1 1
OUT: 1 1 1 1 0 0 1 0 0 1 0 0 1 1 1
Top Down weights:
1 1 1 1 0 0 1 0 0 1 0 0 1 1 1
Bottom up weights:
0.200000 0.200000 0.200000 0.20000
www.eeworm.com/read/245261/12807762
out art001.out
BEST NEURON:0
IN: 1 1 1 1 0 0 1 0 0 1 0 0 1 1 1
OUT: 1 1 1 1 0 0 1 0 0 1 0 0 1 1 1
Top Down weights:
1 1 1 1 0 0 1 0 0 1 0 0 1 1 1
Bottom up weights:
0.200000 0.200000 0.200000 0.20000
www.eeworm.com/read/331336/12832413
m trimmedmse.m
function [cost,retained] = trimmedmse(R,beta,V);
% Calculate trimmed mean of the squared value of the residuals.
%
% cost = trimmedmse(R);
%
% The factor where one trimms off the normed residuals is
www.eeworm.com/read/330850/12865129
m genetic_culling.m
function [patterns, targets, pattern_numbers] = genetic_culling(patterns, targets, params)
% Culling type genetic algorithm for feature selection
%
% Inputs:
% train_patterns - Input patterns
%
www.eeworm.com/read/143365/12881317
out art002.out
BEST NEURON:0
IN: 1 1 1 1 0 0 1 0 0 1 0 0 1 1 1
OUT: 1 1 1 1 0 0 1 0 0 1 0 0 1 1 1
Top Down weights:
1 1 1 1 0 0 1 0 0 1 0 0 1 1 1
Bottom up weights:
0.200000 0.200000 0.200000 0.20000