| PRTools contents |
FEATSELF
[W,R] = FEATSELF(A,CRIT,K,T,FID)
[W,R] = FEATSELF(A,CRIT,K,N,FID)
| Input | |
| A | Training dataset |
| CRIT | Name of the criterion or untrained mapping (default: 'NN', i.e. the 1-Nearest Neighbor error) |
| K | Number of features to select (default: K = 0, return optimal set) |
| T | Tuning dataset (optional) |
| N | Number of cross-validations (optional) |
| FID | File ID to write progress to (default [], see PRPROGRESS) |
| Output | |
| W | Output feature selection mapping |
| R | Matrix with step-by-step results |
Forward 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 using B*W. 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, featselb, featseli, featselp, featselm, prprogress,
| PRTools contents |