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Title: Combining topographic map formation with projection pursuit learning for nonparametric regression analysis
Authors: Van Hulle, Marc # ×
Issue Date: 1996
Publisher: KLUWER ACADEMIC PUBL
Series Title: Neural processing letters vol:4 issue:2 pages:97-105
Conference: date:KATHOLIEKE UNIV LEUVEN,NEURO & PSYCHOFYSIOL LAB,B-3000 LOUVAIN,BELGIUM
Abstract: The original Self-Organizing Map (SOM) algorithm is known to perform poorly on regression problems due to the occurrence of nonfunctional mappings. Recently, we have introduced an. unsupervised learning rule, called the Maximum Entropy learning Rule (MER), which performs topographic map formation without using a neighborhood function. In the present paper, MER is extended with a neighborhood function and applied to nonparametric projection pursuit regression. The extended rule, called eMER, alleviates the occurrence of nonfunctional mappings. The performance of our regression procedure is quantified and compared to other neural network-based parametric and nonparametric regression procedures.
ISSN: 1370-4621
Publication status: published
KU Leuven publication type: IT
Appears in Collections:Research Group Neurophysiology
× corresponding author
# (joint) last author

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