Title :
Structural learning and its applications to rule extraction
Author :
Ishikawa, Masumi
Author_Institution :
Dept. of Control Eng. & Sci., Kyushu Inst. of Technol., Fukuoka, Japan
fDate :
27 Jun-2 Jul 1994
Abstract :
The article presents the concept of structural learning with forgetting. To evaluate its effectiveness, various examples are tried, such as the discovery of a Boolean function and the classification of iris. Its extension to recurrent networks is also described. A database on mushrooms is used to demonstrate the effectiveness of rule extraction from training data. A comparative study on the performance of various structural learning methods is also reported
Keywords :
knowledge acquisition; knowledge based systems; learning (artificial intelligence); neural nets; Boolean function; database; forgetting; iris classification; recurrent networks; rule extraction; structural learning; training data; Boolean functions; Computer networks; Control engineering; Data mining; Databases; Iris; Learning systems; Training data;
Conference_Titel :
Neural Networks, 1994. IEEE World Congress on Computational Intelligence., 1994 IEEE International Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-1901-X
DOI :
10.1109/ICNN.1994.374189
