FEATSELLR

Plus-L-takeaway-R feature selection for classification

   [W,RES] = FEATSELLR(A,CRIT,K,L,R,T)
   [W,RES] = FEATSELLR(A,CRIT,K,L,R,N)

Input
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)
L	Number of features to select at a time (plus-L, default: 1), L ~= R
R	Number of features to deselect at a time (takeaway-R, default: 0)
T	Tuning set (optional)
N	Number of cross-validation folds (optional)

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

Description

Floating selection of K features using the dataset A, by iteratively  selecting L optimal features and deselecting R. Starts from the full  set of features when L < R, otherwise from the empty set. CRIT sets the  criterion used by the feature evaluation routine FEATEVAL. If the dataset  T is given, it is used as a tuning set for FEATEVAL. Alternatively  a number of cross-validations N may be supplied. For K = 0, the optimal  feature set (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

     RES(:,1)            : number of features
     RES(:,2)            : criterion value
     RES(:,3:3+max(L,R)) : added / deleted features

See also

mappings, datasets, feateval, featsel, featselo, featselb, featself, featseli, featselp, featselm, prprogress,