Title :
A neural net based approach for extracting rules from symbolic data
Author :
Nagabhushana, T.N. ; Nijagunarya, Y.S.
Author_Institution :
Dept. of Comput. Sci. & Eng., Sri Jayachamarajendra Coll. of Eng., India
Abstract :
This paper presents a neural network approach for extracting classification rules from symbolic type of data. A scheme for generating data for the neural network training is proposed. The neural network employed is a constructive learning neural network known as resource allocation network (RAN). This network learns very fast and exhibits good response to incoming test pattern making it suitable for rule extraction applications in data mining.
Keywords :
data analysis; data mining; feature extraction; learning (artificial intelligence); neural nets; resource allocation; symbol manipulation; RAN; constructive learning; data mining; neural network training; resource allocation network; symbolic data; Computer science; Data analysis; Data engineering; Data mining; Educational institutions; Joining processes; Neural networks; Radio access networks; Resource management; Testing;
Conference_Titel :
Information, Communications and Signal Processing, 2003 and Fourth Pacific Rim Conference on Multimedia. Proceedings of the 2003 Joint Conference of the Fourth International Conference on
Print_ISBN :
0-7803-8185-8
DOI :
10.1109/ICICS.2003.1292611
