A Genetic Prototype Learner
Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence. Genetic Algorithms. Pages 725-732.
Abstract
Supervised classification problems have received considerable attention from the machine learning community. We propose a novel genetic algorithm based prototype learning system, PLEASE, for this class of problems. Given a set of prototypes for each of the possible classes, the class of an input instance is determined by the prototype nearest to this instance. We assume ordinal attributes and prototypes are represented as sets of feature-value pairs. A genetic algorithm is used to evolve the number of prototypes per class and their positions on the input space as determined by corresponding feature-value pairs. Comparisons with C4.5 on a set of artificial problems of controlled complexity demonstrate the effectiveness ofthe proposed system .
@inproceedings{ijcai1995p95,
title = {A Genetic Prototype Learner},
author = {Sen, Sandip and Knight, Leslie},
booktitle = {Proceedings of the Fourteenth International Joint Conference on
Artificial Intelligence, {IJCAI-95}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Chris S. Mellish},
pages = {725--732},
year = {1995},
note = {Genetic Algorithms},
url = {https://ijcai.org/proceedings/1995/95},
}
TY - CPAPER TI - A Genetic Prototype Learner AU - Sen, Sandip AU - Knight, Leslie T2 - Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence, IJCAI-95 PB - International Joint Conferences on Artificial Intelligence PY - 1995 SP - 725 EP - 732 UR - https://ijcai.org/proceedings/1995/95 ER -Copied
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