Diferencia entre revisiones de «Relevance Dendritic Computing: codes and examples»

De Grupo de Inteligencia Computacional (GIC)
Sin resumen de edición
Sin resumen de edición
Línea 6: Línea 6:
:Datasets avalaible in:
:Datasets avalaible in:
:[[http://www.fml.tuebingen.mpg.de/Members/raetsch/benchmark/?searchterm=benchmark | Benchmarks datasets]]
:[[http://www.fml.tuebingen.mpg.de/Members/raetsch/benchmark/?searchterm=benchmark | Benchmarks datasets]]
: The details of the method are given in the paper
    ''Learning Parsimonious Dendritic Classifiers''
    M. Graña, and A.I. Gonzalez, Neurocomputing (submitted for publication).


: Some results obtained. Figures shown the distribution of class 1 (blue dot region) obtained by training on the (a) XOR, (b) Gaussians centered at the XOR points, (c) the synthetic data used by Tipping and (d) synthetic ring data.
: Some results obtained. Figures shown the distribution of class 1 (blue dot region) obtained by training on the (a) XOR, (b) Gaussians centered at the XOR points, (c) the synthetic data used by Tipping and (d) synthetic ring data.
Línea 16: Línea 12:


<div align="center">[[Imagen:RDC-synth.png | 250px]]  (c)  [[Imagen:SLKN_ring.png | 250px]]  (d)  </div>
<div align="center">[[Imagen:RDC-synth.png | 250px]]  (c)  [[Imagen:SLKN_ring.png | 250px]]  (d)  </div>
: The details of the method are given in the paper
    ''Learning Parsimonious Dendritic Classifiers''
    M. Graña, and A.I. Gonzalez, Neurocomputing (submitted for publication).


'''Copyright 2011 Grupo Inteligencia Computacional, Universidad del País Vasco / Euskal Herriko Unibertsitatea (UPV/EHU)'''.
'''Copyright 2011 Grupo Inteligencia Computacional, Universidad del País Vasco / Euskal Herriko Unibertsitatea (UPV/EHU)'''.

Revisión del 22:51 9 dic 2011

This page is devoted to publishing code for Relevance Dendritic Computing and some execution examples.

Download the MATLAB code for Relevance Dendritic Computing here:
Download
Datasets avalaible in:
[| Benchmarks datasets]
Some results obtained. Figures shown the distribution of class 1 (blue dot region) obtained by training on the (a) XOR, (b) Gaussians centered at the XOR points, (c) the synthetic data used by Tipping and (d) synthetic ring data.
RDC6 xor.png (a) RDC6 gauss xor.png (b)
RDC-synth.png (c) SLKN ring.png (d)
The details of the method are given in the paper
   Learning Parsimonious Dendritic Classifiers
   M. Graña, and A.I. Gonzalez, Neurocomputing (submitted for publication).

Copyright 2011 Grupo Inteligencia Computacional, Universidad del País Vasco / Euskal Herriko Unibertsitatea (UPV/EHU).