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matlab feature ranking

used function rankfeatures (consider sample as column)
====================================================

train = [trainFeature trainLabel];
[IDX ,Z] = rankfeatures(trainFeature' ,trainLabel' ,'Criterion', 'ttest'); 
%ttest / entropy/ etc...





topRankedFeature = (size(trainLabel,1)) / 2 ; 



classify( testFeature( :,IDX(1:topRankedFeature) ),   ...

          trainFeature( :,IDX(1:topRankedFeature) ), trainLabel, ...     'diagquadratic' ) % liner/quadratic/diagquadratic etc






% transpose as it takes sample as column vector


%ttest / entropy/ etc...  


%IDX is the list of indices to the rows in X with the most significant features.  


%Z is the absolute value of the criterion used (see below) 





 







































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