代码搜索：classification
找到约 3,679 项符合「classification」的源代码
代码结果 3,679
www.eeworm.com/read/487815/6500668
m softmargin.m
function y = softmargin(x)
%SOFTMARGIN Support Vector Classification Softmargin
%
% Usage: y = softmargin(x)
%
% Author: Steve Gunn (srg@ecs.soton.ac.uk)
if (nargin ~= 1) % check correct number o
www.eeworm.com/read/487843/6501076
m softmargin.m
function y = softmargin(x)
%SOFTMARGIN Support Vector Classification Softmargin
%
% Usage: y = softmargin(x)
%
% Author: Steve Gunn (srg@ecs.soton.ac.uk)
if (nargin ~= 1) % check correct number o
www.eeworm.com/read/487120/6515346
m fun_custo_nn.m
function Fit = fun_custo_nn(x,C)
z=1;
for i=1:length(x)
if (x(i) == 1)
caract(:,z)=C(:,i);
z=z+1;
end
end
benigno = C(:,(length(x)+1))==0;
normal = C(:,(length(x)+1)
www.eeworm.com/read/476885/6753822
m codice_b.m
%
% In order to obtain a simple and effective source code for
% Fingerprint Recognition System please visit
% http://utenti.lycos.it/matlab/beginner.htm
%
% There you will be able to make a sma
www.eeworm.com/read/476497/6754607
java reseausomcolor.java
package somcolorapp;
/**
* Package somcolorapp
* Classification des couleurs avec un r閟eau de Kohonen.
* R閟eaux Neauronaux, Vuibert 2006.
* Jean-Philippe Rennard
* version 1.0, 17/3/2006
www.eeworm.com/read/263805/11341579
m contents.m
% Neural Network Design Demonstrations.
% Copyright (c) 1994 by PWS Publishing Company.
%
% General
% nnd - Splash screen.
% nndtoc - Table of contents.
% nnsound - Turn Neural Net
www.eeworm.com/read/406594/11439425
m contents.m
% Neural Network Design Demonstrations.
% Copyright (c) 1994 by PWS Publishing Company.
%
% General
% nnd - Splash screen.
% nndtoc - Table of contents.
% nnsound - Turn Neural Net
www.eeworm.com/read/402781/11527370
txt word-list.txt
above
abuse
accident
accord
account
accounting
acoustic
action
activex
adams
adderss
adolescent
adult
adults
advantage
advertising
affirmative
african
agco
agency
aging
agreement
agricultural
agrresiv
www.eeworm.com/read/400577/11572657
m bpxnc.m
%BPXNC Back-propagation trained feed-forward neural net classifier
%
% [W,HIST] = BPXNC (A,UNITS,ITER,W_INI,T,FID)
%
% INPUT
% A Dataset
% UNITS Array indicating number of units in each h
www.eeworm.com/read/400398/11577564
java trainingdatamanager.java
package com.vista;
import java.io.BufferedReader;
import java.io.File;
import java.io.FileInputStream;
import java.io.FileNotFoundException;
import java.io.IOException;
import java.io.InputStr