Computer Science – Neural and Evolutionary Computing
Scientific paper
2007-12-21
Biological and Artificial Computation: From Neuroscience to Technology, J.Mira, R.Moreno-Diaz, J.Cabestany (eds.), pp. 607-616
Computer Science
Neural and Evolutionary Computing
10 pages, 1 figure, 3 tables
Scientific paper
In this paper we shall review the common problems associated with Piecewise Linear Separation incremental algorithms. This kind of neural models yield poor performances when dealing with some classification problems, due to the evolving schemes used to construct the resulting networks. So as to avoid this undesirable behavior we shall propose a modification criterion. It is based upon the definition of a function which will provide information about the quality of the network growth process during the learning phase. This function is evaluated periodically as the network structure evolves, and will permit, as we shall show through exhaustive benchmarks, to considerably improve the performance(measured in terms of network complexity and generalization capabilities) offered by the networks generated by these incremental models.
Cabestany Joan
de Lara Alejandro Chinea Manrique
Madrenas Arostegui Jordi
Moreno Juan Manuel
No associations
LandOfFree
Improving the Performance of PieceWise Linear Separation Incremental Algorithms for Practical Hardware Implementations does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with Improving the Performance of PieceWise Linear Separation Incremental Algorithms for Practical Hardware Implementations, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Improving the Performance of PieceWise Linear Separation Incremental Algorithms for Practical Hardware Implementations will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-696611