An Empirical Comparison of ID3 and Back-propagation
Proceedings of the Eleventh International Joint Conference on Artificial Intelligence. Machine Learning. Pages 788-792.
Abstract
AI and connectionist approaches to learning from examples differ in knowledge-base representation and inductive mechanisms. To explore these differences we experiment with a system from each paradigm: ID3 and back-propagation. We compare the systems on the basis of both prediction accuracy and length of training . The systems show distinct performance differences across a variety of domains. We identify aspects of each system that may account for these performance differences. Finally, we suggest paths for cross-paradigm interaction.
@inproceedings{ijcai1989p126,
title = {An Empirical Comparison of ID3 and Back-propagation},
author = {Fisher, Douglas H. and McKusick, Kathleen B.},
booktitle = {Proceedings of the Eleventh International Joint Conference on
Artificial Intelligence, {IJCAI-89}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {N. S. Sridharan},
pages = {788--792},
year = {1989},
month = {8},
note = {Machine Learning},
url = {https://ijcai.org/proceedings/1989/126},
}
TY - CPAPER TI - An Empirical Comparison of ID3 and Back-propagation AU - Fisher, Douglas H. AU - McKusick, Kathleen B. T2 - Proceedings of the Eleventh International Joint Conference on Artificial Intelligence, IJCAI-89 PB - International Joint Conferences on Artificial Intelligence PY - 1989 SP - 788 EP - 792 UR - https://ijcai.org/proceedings/1989/126 ER -Copied
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