function?testClassPredicted=bootstrapnnlsClassifier（trainSettrainClasstestSettestClassoption）
%?Bootstrap?NNLS?Classifier:?testSet=trainSet*Y?s.t.?Y>=0.
%?Usage:
%?[testClassPredictedsparsity]=bootstrapnnlsClassifier（trainSettrainClass[]testClass）
%?[testClassPredictedsparsity]=bootstrapnnlsClassifier（trainSettrainClasstestSettestClass）
%?[testClassPredictedsparsity]=bootstrapnnlsClassifier（trainSettrainClasstestSettestClassoption）
%?trainSet?matrix?the?training?set?with?samples?in?columns?and?features?in?rows.
%?trainClass:?column?vector?of?numbers?or?string?the?class?labels?of?the?traning?set.
%?testSet:?matrix?the?test?set.
%?testClass:?column?vector?of?numbers?or?string?the?class?labels?of?the
%?test/unknown?set.?It?is?actually?unused?in?this?function?thus?set?it?[].
%?option:?struct?the?options?to?configue?this?function:
%?option.method?string?the?optimization?algorithm?used?to?solve?the?NNLS?problem.?It?could?be
%?????‘nnls‘:?used?the?NNLS?algorithm?（default）;
%?????‘seminmfupdaterule‘:?use?the?update?rules?based?algorithm;
%?????‘sparsennls‘:?used?NNLS?algorithm?with?sparse?constraint.
%?option.predicter:?the?method?to?find?the?class?label?of?a?test?sample?according?to?Y.?It?could?be
%?????‘max‘:?the?same?class?label?with?the?training?sample?with?the?maximum?coefficient?（default）;
%?????‘kvote‘:?select?k?training?samples?with?the?k?largest?coefficients?and?decide?the?class?labels?by?majority?voting.
%?option.kernel?string?specifies?the?kernel.?can?be?‘linear‘（default）‘polynomial‘‘rbf‘‘sigmoid‘‘ds‘
%?option.param?scalar?or?column?vector?the?parameters?for?kernels?the?default?is?[].
%?option.kernelParamRandomAssign:?logical?if?randomly?assign?the
%?parameters?the?default?is?false.
%?option.k:?scalar?only?for?option.predicter=‘kvote‘.?The?default?is?1.
%?option.numRandom?scalar?the?times?to?use?bootstrapping.?The?default?is?99.
%?testClassPredicted:?column?vector?the?predicted?class?labels?of?the?test/unknown?samples.
%?sparsity:?scalar?the?sparsity?of?the?coefficient?matrix?Y.
%?References:
%??[1]\bibitem{nips2011}
%?????Y.?Li?and?A.?Nogm
%?????‘‘Non-neagtive?least?squares?classifier‘‘
%?????{\it?Advances?in?Neural?Information?Processing?Systems}
%?????submitted.?
%?????Available?at?\url{http://cs.uwindsor.ca/~li11112c/doc/nips2011.pdf}
%?Contact?Information:
%?Yifeng?Li
%?University?of?Windsor
%?li11112c@uwindsor.ca;?yifeng.li.cn@gmail.com
%?May?23?2011



if?nargin<5
???option=[];?
end
optionDefault.method=‘nnls‘;
optionDefault.predicter=‘max‘;
optionDefault.kernel=‘linear‘;
optionDefault.param=[];
optionDefault.kernelParamRandomAssign=false;
optionDefault.k=1;
optionDefault.numRandom=99;
option=mergeOption（optionoptionDefault）;

trainSetOrigin=trainSet;
trainClassOrigin=trainClass;
testSetOrigin=testSet;

if?size（trainSetOrigin3）>1?%?tensor
????trainSetOrigin=matrizicing（trainSetOrigin3）;
????testSet=matrizicing（testSetOrigin3

?屬性????????????大小?????日期????時間???名稱
-----------?---------??----------?-----??----
?????目錄???????????0??2015-03-07?07:27??srv1_9\
?????文件????????3508??2015-03-02?21:56??srv1_9\readMe.txt
?????文件?????????509??2015-03-02?20:47??srv1_9\exampleUSR.m
?????文件?????????858??2013-02-14?20:23??srv1_9\wvote.m
?????文件????????7186??2015-03-07?07:10??srv1_9\vsmf.m
?????文件?????????821??2011-10-11?17:00??srv1_9\vote.m
?????文件?????????290??2010-09-28?04:54??srv1_9\vec2mat.m
?????文件????????4308??2013-02-23?00:12??srv1_9\usr.m
?????文件????????1397??2011-10-11?17:10??srv1_9\unmatrizicing.m
?????文件????????4116??2013-02-04?09:04??srv1_9\threeDSearchUniverse.m
?????文件????????1975??2013-07-11?02:27??srv1_9\subspace.m
?????文件????????3170??2015-03-02?18:45??srv1_9\SRC2.m
?????文件????????3150??2011-12-17?02:32??srv1_9\src.m
?????文件?????????372??2013-07-11?00:07??srv1_9\sparsity.m
?????文件????????1450??2012-01-12?02:46??srv1_9\sparsenmfnnlstest.m
?????文件????????7046??2012-11-11?21:25??srv1_9\softSVMTrain2.m
?????文件????????2178??2012-09-15?23:53??srv1_9\softSVMPredict2.m
?????文件????????3206??2012-11-25?08:53??srv1_9\significantAcc.m
?????文件?????????961??2011-11-19?03:51??srv1_9\sampleSelNNLS.m
?????文件?????????493??2011-11-19?04:03??srv1_9\sampleSelKNN.m
?????文件?????????570??2011-10-11?16:43??srv1_9\pseudoinverse.m
?????文件?????????486??2013-04-04?06:19??srv1_9\proximalOperator.m
?????文件?????????399??2012-04-04?22:35??srv1_9\plotTime.m
?????文件????????1795??2012-11-25?08:59??srv1_9\plotNemenyiTest.m
?????文件????????1808??2012-04-05?07:03??srv1_9\plotDataMulti.m
?????文件????????2525??2013-02-19?22:13??srv1_9\plotBarError.m
?????文件????????4100??2012-08-10?00:12??srv1_9\perform.m
?????文件?????????869??2011-10-11?17:14??srv1_9\normmean0std1.m
?????文件?????????175??2011-11-19?03:35??srv1_9\normcl1.m
?????文件?????????393??2012-02-17?09:22??srv1_9\normalizeKernelMatrix.m
?????文件?????????248??2013-05-22?23:09??srv1_9\NNQPSMOMulti.m
............此處省略100個文件信息