function?[svm_struct?svIndex]?=?svmtrain_lm（training?groupnames?varargin）
%SVMTRAIN?trains?a?support?vector?machine?classifier
%
%???SVMStruct?=?SVMTRAIN（TRAININGGROUP）?trains?a?support?vector?machine
%???classifier?using?data?TRAINING?taken?from?two?groups?given?by?GROUP.
%???SVMStruct?contains?information?about?the?trained?classifier?including
%???the?support?vectors?that?is?used?by?SVMCLASSIFY?for?classification.
%???GROUP?is?a?column?vector?of?values?of?the?same?length?as?TRAINING?that
%???defines?two?groups.?Each?element?of?GROUP?specifies?the?group?the
%???corresponding?row?of?TRAINING?belongs?to.?GROUP?can?be?a?numeric
%???vector?a?string?array?or?a?cell?array?of?strings.?SVMTRAIN?treats
%???NaNs?or?empty?strings?in?GROUP?as?missing?values?and?ignores?the
%???corresponding?rows?of?TRAINING.
%
%???SVMTRAIN（...‘KERNEL_FUNCTION‘KFUN）?allows?you?to?specify?the?kernel
%???function?KFUN?used?to?map?the?training?data?into?kernel?space.?The
%???default?kernel?function?is?the?dot?product.?KFUN?can?be?one?of?the
%???following?strings?or?a?function?handle:
%
%???????‘linear‘??????Linear?kernel?or?dot?product
%???????‘quadratic‘???Quadratic?kernel
%???????‘polynomial‘??Polynomial?kernel?（default?order?3）
%???????‘rbf‘?????????Gaussian?Radial?Basis?Function?kernel
%???????‘mlp‘?????????Multilayer?Perceptron?kernel?（default?scale?1）
%???????‘mix‘?????????mlp+rbf
%???????function??????A?kernel?function?specified?using?@
%?????????????????????for?example?@KFUN?or?an?anonymous?function
%
%???A?kernel?function?must?be?of?the?form
%
%?????????function?K?=?KFUN（U?V）
%
%???The?returned?value?K?is?a?matrix?of?size?M-by-N?where?U?and?V?have?M
%???and?N?rows?respectively.??If?KFUN?is?parameterized?you?can?use
%???anonymous?functions?to?capture?the?problem-dependent?parameters.?For
%???example?suppose?that?your?kernel?function?is
%
%???????function?k?=?kfun（uvp1p2）
%???????k?=?tanh（p1*（u*v‘）+p2）;
%
%???You?can?set?values?for?p1?and?p2?and?then?use?an?anonymous?function:
%???????@（uv）?kfun（uvp1p2）.
%
%???SVMTRAIN（...‘RBF_SIGMA‘SIGMA）?allows?you?to?specify?the?scaling
%???factor?sigma?in?the?radial?basis?function?kernel.
%
%???SVMTRAIN（...‘POLYORDER‘ORDER）?allows?you?to?specify?the?order?of?a
%???polynomial?kernel.?The?default?order?is?3.
%
%???SVMTRAIN（...‘MLP_PARAMS‘[P1?P2]）?allows?you?to?specify?the
%???parameters?of?the?Multilayer?Perceptron?（mlp）?kernel.?The?mlp?kernel
%???requires?two?parameters?P1?and?P2?where?K?=?tanh（P1*U*V‘?+?P2）?and?P1
%???>?0?and?P2?%
%???SVMTRAIN（...‘METHOD‘METHOD）?allows?you?to?specify?the?method?used
%???to?find?the?separating?hyperplane.?Options?are
%
%???????‘QP‘??Use?quadratic?programming?（requires?the?Optimization?Toolbox）
%???????‘SMO‘?Use?Sequential?Minimal?Optimization?method
%???????‘LS‘??Use?least-squares?method
%
%???If?you?have?the?Optimization?Toolbox?then?the?QP?method?is?the?defau

?屬性????????????大小?????日期????時間???名稱
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?????文件???????22907??2013-07-31?11:35??svmtrain_lm.m