| PRTools contents |
PARZENM
W = PARZENM(A,H)
W = A*PARZENM([],H)
D = B*W
| Input | |
| A | Input dataset |
| H | Smoothing parameters (scalar, vector) |
| Output | |
| W | output mapping |
A Parzen distribution is estimated for the labeled objects in A. Unlabeled objects are neglected, unless A is entirely unlabeled or double. Then all objects are used. If A is a multi-class dataset the densities are estimated class by class and then weighted and combined according their prior probabilities. In all cases, just single density estimator W is computed.
The mapping W may be applied to a new dataset B using DENSITY = B*W.
The smoothing parameter H is estimated by PARZENML if not supplied. It can be a scalar or a vector with as many components as A has features.
datasets, mappings, knnm, gaussm, parzenml, parzendc, knnm,
| PRTools contents |