| PRTools contents |
FEATSELP
[W,R] = FEATSELP(A,CRIT,K,T,FID)
| Input | |
| A | Training dataset |
| CRIT | Name of the criterion or untrained mapping (default: 'NN', 1-Nearest Neighbor error) |
| K | Number of features to select (default: K = 0, select optimal set) |
| T | Tuning dataset (optional) |
| N | Number of cross-validations (optional) |
| FID | File ID to write progress to (default [], see PRPROGRESS) |
| Output | |
| W | Feature selection mapping |
| R | Matrix with step-by-step results |
Forward floating 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. 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 in a dataset B using B*W. The selected features are stored in W.DATA and can be found by +W.
Note: this routine is highly time consuming.
In R the search is reported step by step
R(:,1) : number of features
R(:,2) : criterion value
R(:,3) : added / deleted feature
mappings, datasets, feateval, featselo, featselb, featseli,
| FEATSEL, | FEATSELF, FEATSELM, PRPROGRESS |
| PRTools contents |