Title :
Learning fuzzy hyper-rectangles with instance and neural based methods
Author :
Figueira, Lucas Baggio ; Lisboa, Flávia O S Sá ; Do Carmo Nicoletti, Maria
Author_Institution :
Dept. de Comput. Sci., Univ. Fed. de Sao Carlos, Sao Paulo, Brazil
Abstract :
The NGE model is an instance-based inductive learning method that generalizes a given training set into hypotheses represented as a set of hyper-rectangles in a n-dimensional Euclidean space. The RuleNet model does exactly the same thing, but using a neural network algorithm. This paper focuses on a fuzzy version of both algorithms aiming at comparing their performances.
Keywords :
feedforward neural nets; fuzzy set theory; generalisation (artificial intelligence); learning by example; RuleNet; feedforward constructive neural network; fuzzy hyper rectangles; fuzzy membership function; instance based inductive learning method; n-dimensional Euclidean space; nested generalised exemplar model; neural network algorithm; supervised machine learning; training set; Computer science; Euclidean distance; Feedforward neural networks; Feedforward systems; Learning systems; Nearest neighbor searches; Neural networks; Proposals; Shape;
Conference_Titel :
Fuzzy Information, 2004. Processing NAFIPS '04. IEEE Annual Meeting of the
Print_ISBN :
0-7803-8376-1
DOI :
10.1109/NAFIPS.2004.1336327
