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FEATSELB
[W,R] = FEATSELB(A,CRIT,K,T,FID)
[W,R] = FEATSELB(A,CRIT,K,N,FID)
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) |
T | Tuning set (optional) |
N | Number of cross-validations |
FID | File ID to write progress to (default [], see PRPROGRESS) |
Output | |
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
mappings, datasets, feateval, featsellr, featsel, featselo, featself, featseli, featselp, featselm, prprogress,
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