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Trainable mapping for backward feature selection

    [W,R] = A*FEATSELB([],CRIT,K,T)
    [W,R] = A*FEATSELB([],CRIT,K,N)

 A Dataset
 CRIT String name of the criterion or untrained mapping  (optional; default: 'NN', i.e. 1-Nearest Neighbor error)
 K Number of features to select  (optional; default: return optimally ordered set of all features)
 T Tuning set (optional)
 N Number of cross-validation folds

 W Output feature selection mapping
 R Matrix with step-by-step results of the selection


Backward selection of K features using the dataset A. CRIT sets the  criterion used by the feature evaluation routine FEATEVAL. If the  dataset T is given, it is used as test set for FEATEVAL. Alternatvely a  a number of cross-validation N may be supplied. For K = 0, the optimal  feature set (corresponding to the maximum value of FEATEVAL) is returned.  The result W can be used for selecting features by B*W. In this case,  features are ranked optimally.  The selected features are stored in W.DATA and can be found by +W.  In R, the search is reported step by step as

     R(:,1) : number of features
     R(:,2) : criterion value
     R(:,3) : added / deleted feature

See also

mappings, datasets, feateval, featsellr, featsel, featselo, featself, featseli, featselp, featselm,

PRTools Contents

PRTools User Guide

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