A new learning method for piecewise linear regression. ICANN (2002)
| Citations: | 4 - 0 self |
BibTeX
@MISC{Ferrari-trecate02anew,
author = {Giancarlo Ferrari-trecate and Marco Muselli},
title = {A new learning method for piecewise linear regression. ICANN},
year = {2002}
}
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Abstract
Abstract. A new connectionist model for the solution of piecewise linear regression problems is introduced; it is able to reconstruct both continuous and non continuous real valued mappings starting from a finite set of possibly noisy samples. The approximating function can assume a different linear behavior in each region of an unknown polyhedral partition of the input domain. The proposed learning technique combines local estimation, clustering in weight space, multicategory classification and linear regression in order to achieve the desired result. Through this approach piecewise affine solutions for general nonlinear regression problems can also be found. 1
Citations
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| 10 | Nonlinear adaptive control using networks of piecewise linear approximators - Choi, Farrell - 2000 |
| 8 | Constructive neural networks with piecewise interpolation capabilities for function approximation - Choi, Choi - 1994 |
| 4 | A structure trainable neural network with embedded gating units and its learning algorithm - Nakayama, Hirano, et al. - 2000 |
