DocumentCode
296112
Title
On the mapping of linear classification trees onto one-hidden-layer neural nets
Author
Bioch, Jan C. ; Carsouw, Robert ; Potharst, Rob
Author_Institution
Dept. of Comput. Sci., Erasmus Univ., Rotterdam, Netherlands
Volume
4
fYear
1995
fDate
Nov/Dec 1995
Firstpage
1739
Abstract
In this paper we show that the convex regions induced by a decision tree with linear decision function cannot be represented by linear membership functions as suggested in the literature. It appears that a faithful representation is only possible for subregions. We derive explicit expressions for the membership functions of these subregions. This approximation can be used to initialise a one-hidden-layer neural net
Keywords
decision theory; feedforward neural nets; function approximation; pattern classification; trees (mathematics); approximation; convex regions; decision tree; feedforward neural networks; linear classification trees; linear membership functions; mapping; one-hidden-layer neural nets; Classification tree analysis; Computer science; Convergence; Decision trees; Equations; Feedforward neural networks; Neural networks; Vegetation mapping;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1995. Proceedings., IEEE International Conference on
Conference_Location
Perth, WA
Print_ISBN
0-7803-2768-3
Type
conf
DOI
10.1109/ICNN.1995.488883
Filename
488883
Link To Document