%?adaboost.M1
function?[trerr?tserr?w]?=?adaboostM1（typefea_tr?lab_tr?fea_ts?lab_tsMcnln）
%?perform?adaboost?algorithm?
%?type:?????????????????the?based?classifier
%?fea_tr?lab_tr:???????training?feature?and?label
%?fea_ts?lab_ts:???????testing?feature?and?label
%?M:????????????????????iteration?num
%?cn:???????????????????class?num
%?trerr?????????????????training?error?（combined）
%?tserr?????????????????testing?error
%?w?????????????????????weight?distribution

if?nargin?????disp（‘adaboostM1（type?fea_tr?lab_tr?fea_ts?lab_ts?M?[cn]）‘）;
????return;
elseif?nargin?==?6
????cn?=?2;
end

if?nargout?????w?=?[];
end

%?first?get?parameters
vsize?=?size（fea_tr?1）;
trnum?=?size（fea_tr?2）;
tsnum?=?size（fea_ts?2）;
%?
if?（vsize?~=?size（fea_ts?1））
????disp（‘training?feature?and?testing?feature?donnot?have?same?size\n‘）;
????return;
end

if?（trnum?~=?size（lab_tr?2））
????disp（‘training?set?has?different?feature?and?label?size\n‘）;
????return;
end

if?（tsnum?~=?size（lab_ts?2））
????disp（‘testing?set?has?different?feature?and?label?size\n‘）;
????return;
end

%?deal?with?different?base?classifiers
%?switch?lower（type）
%?????


%?case?‘nearest‘??????????????????????%?nearest?neighbour
????%?parameters
????weight?=?ones（1?trnum）?/?trnum;
????alpha_M?=?zeros（1?M）;
????hypo_tr_M?=?zeros（1?trnum?M）;
????I_tr_M?=?zeros（1?trnum?M）;
????hypo_ts_M?=?zeros（1?tsnum?M）;
????I_ts_M?=?zeros（1?tsnum?M）;
????m?=?1;?err?=?-1;
????trainError=[];
????testError=[];
????%while?m<=M?&?err<0.5?&?err~=0
????while?m<=M
???????

%?????????[fea_trfea_ts]?=?get_sample（ln）;
????????
?????????%?resample?data
????????[fea_w?lab_w?idx_w]?=?resample（fea_tr?lab_tr?weight）;
????????
????????%?train?base?classifier?and?run?base?classifier?on?ORIGINAL?trainning?data?I==1?means?wrongly?classified
????????%?for?KNN?it?requires?only?one?step
????????if?strcmp（type‘bayes‘）
????????[I_tr?hypo_tr]?=?bayes（fea_w?lab_w?fea_tr?lab_tr）;????????%?train?on?training?set
????????[I_ts?hypo_ts]?=?bayes（fea_w?lab_w?fea_ts?lab_ts）;????????%?train?on?testing?set
????????end
????????
????????if?strcmp（type‘knn‘）
????????[I_tr?hypo_tr]?=?knn（fea_w?lab_w?fea_tr?lab_tr）;????????%?train?on?training?set
????????[I_ts?hypo_ts]?=?knn（fea_w?lab_w?fea_ts?lab_ts）;????????%?train?on?testing?set
????????end
????????%?calculate?err
????????err?=?sum（weight?.*?I_tr?2）?/?sum（weight?2）;
????????
????????%?calculate?alpha
????????alpha_M（m）?=?0.5*log（（1-err）/err）;
????????
????????%?update?weight
????????weight?=?weight?.*?exp（2*alpha_M（m）*I_tr）;
????????weight?=?weight?./?sum（weight2）;
????????
????????%?store?parameters?for?round?m
????????hypo_tr_M（:?:?m）?=?hypo_tr;
????????hypo_ts_M（:?:?m）?=?hypo_ts;
????????I_tr_M（:?:?m）?=?I_tr;
????????I_ts_M（:?:?m）?=?I_ts;
????????
????????%?update?m
????????m?=?m?+?1;
????????
????end

????%?show?debug?information
%???

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

?????文件???????4019??2015-05-11?20:20??adaboost+bayes\adaboostM1.m

?????文件????????250??2015-05-11?17:29??adaboost+bayes\bayes.m

?????文件????????857??2015-05-11?21:05??adaboost+bayes\compareKNNAndNavibayes.m

?????文件?????145268??2015-05-11?17:57??adaboost+bayes\data.mat

?????文件???????1602??2015-05-11?17:58??adaboost+bayes\generateTrainTestSamples.m

?????文件????????816??2015-05-11?21:05??adaboost+bayes\main.m

?????文件????????116??2015-05-11?17:52??adaboost+bayes\normalData.m

?????文件???????1253??2015-05-11?16:30??adaboost+bayes\resample.m

?????文件???????8050??2015-05-11?21:04??adaboost+bayes\對比.fig

?????文件???????7856??2015-05-11?20:24??adaboost+bayes\錯誤率.fig

?????目錄??????????0??2015-05-11?21:13??adaboost+bayes

-----------?---------??----------?-----??----

???????????????170087????????????????????11