mytest.m

来自「一个关于adaboost算法的matlab程序,对开始接触adaboost研究的」· M 代码 · 共 36 行

%   G. Raetsch 15.2.99
%
%   Copyright (c) 1998  GMD Berlin - All rights reserved
%   THIS IS UNPUBLISHED PROPRIETARY SOURCE CODE of GMD FIRST Berlin
%   The copyright notice above does not evidence any
%   actual or intended publication of this work.
%
% for terms of usage see COPYRIGHTS.TXT
%
% example for a classification task

num_train=70 ;
num_test=1000 ;
lnoise=0.1 ;  % amount of label noise in the data

X=randn(2,num_train+num_test) ;
Y=((X(1,:).^2+X(2,:).^2)<1)-((X(1,:).^2+X(2,:).^2)>=1) ;

% splitting: training and test data
idx=randperm(num_train+num_test) ;
XT=X(:,idx(1:num_train)) ;
YT=Y(1,idx(1:num_train)) ; 
XTE=X(:,idx(num_train+1:num_train+num_test)) ;
YTE=Y(1,idx(num_train+1:num_train+num_test)) ;

% 'add' some label noise
YT(1:floor(lnoise*num_train))=-YT(1:floor(lnoise*num_train)) ;

% create object 'data'
dataset=data(XT, YT, XTE, YTE) ;
dataset 
% create a plain rbf net with 10 centers, regularization 1e-4, 
%                                input dimension = two
%                                output dimension = one
rn=rbf_net_w(10, 1e-4, 2, 1) ;
rn=set_max_iter(rn, 0) ;