CART/CMAC hybrid: regression trees with interpolation

Author

Prager, Richard W.

Author_Institution

Dept. of Eng., Cambridge Univ., UK

Volume

2

fYear

1994

fDate

9-13 Oct 1994

Firstpage

476

Abstract

This paper presents a new algorithm for non-linear regression. It involves combining a modified regression tree with a CMAC network in a way which retains the most desirable properties of both these algorithms. The new algorithm is compared with a conventional regression tree as described in the CART book (Breiman et al., 1984). It consistently performs better on the Boston Housing Data task. The CMAC consists of a fixed non-linear mapping followed by a single layer of adaptive links. The non-linear mapping has uniform sensitivity across the whole of the input space. The essence of the new hybrid algorithm is to use a regression tree to produce a more efficient design for the CMAC non-linear mapping

Keywords

cerebellar model arithmetic computers; Boston Housing Data task; CART/CMAC hybrid; adaptive links; modified regression tree; nonlinear mapping; nonlinear regression; regression trees with interpolation; Algorithm design and analysis; Books; Error correction; Input variables; Interpolation; Performance evaluation; Prediction algorithms; Predictive models; Regression tree analysis; Testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Pattern Recognition, 1994. Vol. 2 - Conference B: Computer Vision & Image Processing., Proceedings of the 12th IAPR International. Conference on

Conference_Location

Jerusalem

Print_ISBN

0-8186-6270-0

Type

conf

DOI

10.1109/ICPR.1994.576987

Filename

576987