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大小: 1014KB文件類型: .rar金幣: 2下載: 0 次發布日期: 2024-01-27
- 語言: 其他
- 標簽: Matlab??prtools5.2.3??
資源簡介
PRTools can be useful for:
design of prototypes of pattern recognition systems.
design and evaluation of new algorithms.
integration in applied areas of data analysis like computer vision, medical diagnostics, seismics, remote sensing, chemometrics and bio-informatics.
PRTools5.2.3 This has recent

代碼片段和文件信息
%ADABOOSTC
%
%?[WVALF]?=??ADABOOSTC(ACLASSFNRULEVERBOSE);
%
%?INPUT
%???A???????Dataset
%???CLASSF??Untrained?weak?classifier
%???N???????Number?of?classifiers?to?be?trained
%???RULE????Combining?rule?(default:?weighted?voting)
%???VERBOSE?Suppress?progress?report?if?0?(default)
%
%?OUTPUT
%???W???????Combined?trained?classifier
%???V???????Cell?array?of?all?classifiers
%???????????Use?VC?=?stacked(V)?for?combining
%???ALF?????Weights
%
%?DEscriptION
%
%?Computation?of?a?combined?classifier?according?to?adaboost.
%
%?In?total?N?weighted?versions?of?the?training?set?A?are?generated
%?iteratevely?and?used?for?the?training?of?the?specified?classifier.
%?Weights?to?be?used?for?the?probabilities?of?the?objects?in?the?training
%?set?to?be?selected?are?updated?according?to?the?Adaboost?rule.
%
%?The?entire?set?of?generated?classifiers?is?given?in?V.
%?The?set?of?classifier?weigths?according?to?Adaboost?is?returned?in?ALF
%
%?Various?aggregating?possibilities?can?be?given?in?
%?the?final?parameter?rule:
%?[]:??????WVOTEC?weighted?voting.
%?VOTEC????voting
%?MEANC????sum?rule
%?AVERAGEC?averaging?of?coeffients?(for?linear?combiners)
%?PRODC????product?rule
%?MAXC?????maximum?rule
%?MINC?????minimum?rule
%?MEDIANC??median?rule
%
%?REFERENCE
%?Ji?Zhu?Saharon?Rosset?Hui?Zhou?and?Trevor?Hastie?
%?Multiclass?Adaboost.?A?multiclass?generalization?of?the?Adaboost?
%?algorithm?based?on?a?generalization?of?the?exponential?loss.
%?http://www-stat.stanford.edu/~hastie/Papers/samme.pdf
%
%?SEE?ALSO?(PRTools?Guide)
%?MAPPINGS?DATASETS
%?Copyright:?R.P.W.?Duin?r.p.w.duin@37steps.com
%?Faculty?EWI?Delft?University?of?Technology
%?P.O.?Box?5031?2600?GA?Delft?The?Netherlands
%?(Multiclass?correction?by?Marcin?Budka?Bournemouth?Univ.?UK)
%function?[WValf]?=?adaboostc(aclasfnruleverbose)
function?[outValf]?=?adaboostc(varargin)
%%?INITIALISATION
argin?=?setdefaults(varargin[]nmc100[]0);
if?mapping_task(argin‘definition‘)
??
??out?=?define_mapping(argin‘untrained‘‘Adaboost‘);
??
%%?TRAINING
elseif?mapping_task(argin‘training‘)
??
??[aclasfnruleverbose]?=?deal(argin{:});
??[mkc]?=?getsize(a);
??V?=?[];
??laba?=?getlab(a);
??u?=?ones(m1)/m; %?initialise?object?weights
??alf?=?zeros(1n); %?space?for?classifier?weights
??isseparable?=?0;??????????%?check?if?we?can?make?0?error
??if?verbose?&&?k?==?2
????figure(verbose);
????scatterd(a);
??end
??%%?generate?n?classifiers
??for?i?=?1:n
????b?=?gendatw(aum);?????????????%?sample?training?set
????b?=?setprior(bgetprior(a)); %?use?original?priors
????w?=?b*clasf;????????????????????%?train?weak?classifier
????ra?=?a*w;???????????????????????%?test?weak?classifier
????if?verbose?&&?k?==?2
??????plotc(w1);?drawnow
????end
????labc?=?labeld(ra);
????diff?=?sum(labc~=laba2)~=0; %?objects?erroneously?classified
????erra?=?sum((diff).*u);??????????%?weighted?error?on?original?dataset
????if?(erra==0)
????????isseparable?=?1;
????????V?=?
?屬性????????????大小?????日期????時間???名稱
-----------?---------??----------?-----??----
?????文件????????867??2014-12-21?16:37??prtools5.2.3\Install_notes.txt
?????文件???????2635??2012-09-12?13:14??prtools5.2.3\License.txt
?????文件?????????23??2014-12-21?16:39??prtools5.2.3\prtools\@prdatafile\abs.m
?????文件????????115??2014-12-21?16:39??prtools5.2.3\prtools\@prdatafile\abs.p
?????文件????????765??2014-12-21?16:39??prtools5.2.3\prtools\@prdatafile\addpostproc.m
?????文件????????315??2014-12-21?16:39??prtools5.2.3\prtools\@prdatafile\addpostproc.p
?????文件???????1233??2014-12-21?16:39??prtools5.2.3\prtools\@prdatafile\addpreproc.m
?????文件????????377??2014-12-21?16:39??prtools5.2.3\prtools\@prdatafile\addpreproc.p
?????文件?????????23??2014-12-21?16:39??prtools5.2.3\prtools\@prdatafile\and.m
?????文件????????175??2014-12-21?16:39??prtools5.2.3\prtools\@prdatafile\and.p
?????文件?????????97??2014-12-21?16:39??prtools5.2.3\prtools\@prdatafile\check12.m
?????文件????????525??2014-12-21?16:39??prtools5.2.3\prtools\@prdatafile\check12.p
?????文件?????????38??2014-12-21?16:39??prtools5.2.3\prtools\@prdatafile\display.m
?????文件????????413??2014-12-21?16:39??prtools5.2.3\prtools\@prdatafile\display.p
?????文件????????518??2014-12-21?16:39??prtools5.2.3\prtools\@prdatafile\dyadic.m
?????文件????????272??2014-12-21?16:39??prtools5.2.3\prtools\@prdatafile\dyadic.p
?????文件?????????22??2014-12-21?16:39??prtools5.2.3\prtools\@prdatafile\end.m
?????文件????????238??2014-12-21?16:39??prtools5.2.3\prtools\@prdatafile\end.p
?????文件?????????22??2014-12-21?16:39??prtools5.2.3\prtools\@prdatafile\eq.m
?????文件????????175??2014-12-21?16:39??prtools5.2.3\prtools\@prdatafile\eq.p
?????文件?????????23??2014-12-21?16:39??prtools5.2.3\prtools\@prdatafile\exp.m
?????文件????????102??2014-12-21?16:39??prtools5.2.3\prtools\@prdatafile\exp.p
?????文件????????747??2014-12-21?16:39??prtools5.2.3\prtools\@prdatafile\filenames.m
?????文件????????363??2014-12-21?16:39??prtools5.2.3\prtools\@prdatafile\filenames.p
?????文件?????????24??2014-12-21?16:39??prtools5.2.3\prtools\@prdatafile\find.m
?????文件????????203??2014-12-21?16:39??prtools5.2.3\prtools\@prdatafile\find.p
?????文件????????228??2014-12-21?16:39??prtools5.2.3\prtools\@prdatafile\findfiles.m
?????文件????????377??2014-12-21?16:39??prtools5.2.3\prtools\@prdatafile\findfiles.p
?????文件?????????22??2014-12-21?16:39??prtools5.2.3\prtools\@prdatafile\ge.m
?????文件????????179??2014-12-21?16:39??prtools5.2.3\prtools\@prdatafile\ge.p
............此處省略1021個文件信息
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