function?D?=?ada_boost（train_features?train_targets?params?region）;

%?Classify?using?the?AdaBoost?algorithm
%?Inputs:
%?	features	-?Train?features
%	targets	-?Train?targets
%	Params	-?[NumberOfIterations?Weak?Learner?Type?Learner‘s?parameters]
%	region	-?Decision?region?vector:?[-x?x?-y?y?number_of_points]
%
%?Outputs
%	D			-?Decision?sufrace
%
%?NOTE:?This?algorithm?is?very?tuned?to?the?2D?nature?of?the?toolbox!

[k_max?weak_learner?alg_param]?=?process_params（params）;

[NiM]			=?size（train_features）;
D			?		=?zeros（region（5））;
W			?		=?ones（1M）/M;
IterDisp			=?10;

%Find?where?the?training?features?fall?on?the?decision?grid
N???????????=?region（5）;
mx??????????=?ones（N1）?*?linspace?（region（1）region（2）N）;
my??????????=?linspace?（region（3）region（4）N）‘?*?ones（1N）;
flatxy??????=?[mx（:）?my（:）]‘;
train_loc	=?zeros（1M）;
for?i?=?1:M
???dist?=?sqrt（sum（（flatxy?-?train_features（:i）*ones（1N^2））.^2））;
???[m?train_loc（i）]?=?min（dist）;
end

%Do?the?AdaBoosting
for?k?=?1:k_max
???%Train?weak?learner?Ck?using?the?data?sampled?according?to?W:
???%...so?sample?the?data?according?to?W
???randnum?=?rand（1M）;
???cW	???=?cumsum（W）;
???indices?=?zeros（1M）;
???for?i?=?1:M
??????%Find?which?bin?the?random?number?falls?into
??????loc?=?max（find（randnum（i）?>?cW））+1;
??????if?isempty（loc）
?????????indices（i）?=?1;
??????else
?????????indices（i）?=?loc;
??????end
???end
???
???%...and?now?train?the?classifier
???Ck?	=?feval（weak_learner?train_features（:?indices）?train_targets（indices）?alg_param?region）;
???Ckl?	=?Ck（:）;
???
???%Ek?<-?Training?error?of?Ck?
???Ek?=?sum（W.*（Ckl（train_loc）‘?~=?train_targets））;
???
???if?（Ek?==?0）
??????break
???end
???
???%alpha_k?<-?1/2*ln（1-Ek）/Ek）
???alpha_k?=?0.5*log（（1-Ek）/Ek）;
???
???%W_k+1?=?W_k/Z*exp（+/-alpha）
???W??=?W.*exp（alpha_k*（xor（Ckl（train_loc）‘train_targets）*2-1））;
???W??=?W./sum（W）;
???
???%Update?the?decision?region
???D??=?D?+?alpha_k*（2*Ck-1）;
???
???if?（k/IterDisp?==?floor（k/IterDisp））
??????disp（[‘Completed?‘?num2str（k）?‘?boosting?iterations‘]）
???end
???
end

D?=?D>0;

?屬性????????????大小?????日期????時間???名稱
-----------?---------??----------?-----??----

?????文件?????952782??2002-05-20?12:36??mitmatlab\About.bmp

?????文件???????2137??2002-06-25?13:28??mitmatlab\Ada_Boost.m

?????文件???????3004??2002-02-18?18:25??mitmatlab\ADDC.m

?????文件???????4318??2002-03-21?03:43??mitmatlab\AGHC.m

?????文件???????3266??2002-03-21?14:29??mitmatlab\Backpropagation_Batch.m

?????文件???????5183??2002-03-21?14:34??mitmatlab\Backpropagation_CGD.m

?????文件???????6448??2002-03-21?14:31??mitmatlab\Backpropagation_Quickprop.m

?????文件???????4963??2002-03-21?14:34??mitmatlab\Backpropagation_Recurrent.m

?????文件???????3216??2002-03-21?14:33??mitmatlab\Backpropagation_SM.m

?????文件???????2986??2002-03-21?14:33??mitmatlab\Backpropagation_Stochastic.m

?????文件???????1377??2002-03-21?14:38??mitmatlab\Balanced_Winnow.m

?????文件???????3248??2002-03-24?16:32??mitmatlab\Bayesian_Model_Comparison.m

?????文件????????588??2001-12-27?14:56??mitmatlab\Bhattacharyya.m

?????文件???????3298??2002-03-21?14:37??mitmatlab\BIMSEC.m

?????文件???????5977??2005-01-19?12:40??mitmatlab\C4_5.m

?????文件????????758??2001-12-24?21:34??mitmatlab\calculate_error.m

?????文件???????1060??2001-02-22?18:06??mitmatlab\calculate_region.m

?????文件???????4104??2002-03-21?03:43??mitmatlab\CART.m

?????文件????????846??2002-02-10?03:54??mitmatlab\CARTfunctions.m

?????文件???????5443??2002-03-21?14:39??mitmatlab\Cascade_Correlation.m

?????文件????????902??2001-12-27?15:15??mitmatlab\Chernoff.m

?????文件???????1528??2002-02-15?03:59??mitmatlab\chess.mat

?????文件???????2824??2002-07-22?17:37??mitmatlab\Classification.txt

?????文件???????1941??2000-12-27?03:16??mitmatlab\classification_error.m

?????文件??????18356??2005-01-18?18:53??mitmatlab\classifier.m

?????文件???????4328??2002-03-10?04:59??mitmatlab\classifier.mat

?????文件??????25737??2002-05-21?18:25??mitmatlab\classifier_commands.m

?????文件???????2926??2002-02-15?03:59??mitmatlab\click_points.m

?????文件??????86112??2002-02-15?03:59??mitmatlab\clouds.mat

?????文件???????2842??2002-03-21?14:36??mitmatlab\Competitive_learning.m

............此處省略148個文件信息