Update the approximation with one data sample (dummy file).
This file is the basis for implementing learning methods.
Documentation
icl_learn
ILS = icl_learn(ILS, x, y, yp, mode)
Inputs:
| ILS | structure describing the learning system |
| x | double input vector in [-10,10] |
| y | true label, i.e. target value of the example, in [-1, 1] for regression or [-1; 1] for classification |
| yp | predicted label, i.e. current output of the approximation, in [-1, 1] for regression or [-1; 1] for classification |
| mode | operating mode (regression=1, classification=2) |
Outputs:
| ILS | updated matlab structure describing the learning system |
Calls:
Called by:
Authors:
- Andreas Buschermöhle (andbusch(at)uos.de)
Last change: 2013-06-18 - Version 1.5