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Author Colla, V. ♦ Matarese, N. ♦ Reyneri, L.M.
Source IEEE Xplore Digital Library
Content type Text
Publisher Institute of Electrical and Electronics Engineers, Inc. (IEEE)
File Format PDF
Copyright Year ©2009
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Performance evaluation ♦ Filtering ♦ Input variables ♦ Distance evaluation ♦ Supervised learning ♦ Data preprocessing ♦ Fuzzy neural networks ♦ Filtering technique ♦ Function approximation ♦ Intelligent systems ♦ Deductive databases ♦ Fuzzy systems
Abstract When designing a neural or fuzzy system, a careful preprocessing of the database is of utmost importance in order to produce a trustable system. In function approximation applications, when a functional relationship between input and output variables is supposed to exist, the presence of data where the similar set of input variables is associated to very different values of the output is not always beneficial for the final system to design. A method is presented which can be used to detect anomalous data, namely non-coherent associations between input and output patterns. This technique, by mean of a comparison between two distance matrix associated to the input and output patterns, is able to detect elements in a dataset, where similar values of input variables are associated to quite different output values. A numerical example and a more complex application in the pre-processing of data coming from an industrial database were presented.
ISBN 9781424447350
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research ♦ Reading
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2009-11-30
Publisher Place Italy
Rights Holder Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Size (in Bytes) 242.32 kB
Page Count 5
Starting Page 1307
Ending Page 1311


Source: IEEE Xplore Digital Library