Title :
Generalization by humans, neural nets, and ID3
Author :
Bernasconi, J. ; Gustafson, K.
Author_Institution :
Asea Brown Boveri Corp. Res., Baden
Abstract :
Summary form only given, as follows. The authors analyzed an illustrative classification problem suggested by Quinlan and found that humans and neural nets favor a classification rule different from that preferred by the ID3 algorithm. They compared the generalization properties of the three methods and proposed estimating the quality of different classification rules by analyzing the backward prediction ability of the respective generalizations
Keywords :
neural nets; pattern recognition; backward prediction ability; classification rule; generalization properties; illustrative classification problem; neural nets; Algorithm design and analysis; Humans; Mathematics; Neural networks;
Conference_Titel :
Neural Networks, 1991., IJCNN-91-Seattle International Joint Conference on
Conference_Location :
Seattle, WA
Print_ISBN :
0-7803-0164-1
DOI :
10.1109/IJCNN.1991.155559