Noise-Tolerant Windowing
Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence. Learning. Pages 852-858.
Abstract
Windowing has been proposed as a procedure for efficient memory use in the ID3 decision tree learning algorithm. However, it was shown that it may often lead to a decrease in performance, in particular in noisy domains. Following up on previous work, where we have demonstrated that the ability of rule learning algorithms to learn rules independently can be exploited for more efficient windowing procedures, we demonstrate in this paper how this property can be exploited to achieve noisetolerance in windowing.
Johannes Fürnkranz. 1997. Noise-Tolerant Windowing. In Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence, IJCAI-97. IJCAI, 852–858. https://ijcai.org/proceedings/1997/123
Fürnkranz, J. (1997). Noise-Tolerant Windowing. In Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence, IJCAI-97 (pp. 852–858). IJCAI. https://ijcai.org/proceedings/1997/123
@inproceedings{ijcai1997p123,
title = {Noise-Tolerant Windowing},
author = {Fürnkranz, Johannes},
booktitle = {Proceedings of the Fifteenth International Joint Conference on
Artificial Intelligence, {IJCAI-97}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Martha E. Pollack},
pages = {852--858},
year = {1997},
note = {Learning},
url = {https://ijcai.org/proceedings/1997/123},
}
TY - CPAPER TI - Noise-Tolerant Windowing AU - Fürnkranz, Johannes T2 - Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence, IJCAI-97 PB - International Joint Conferences on Artificial Intelligence PY - 1997 SP - 852 EP - 858 UR - https://ijcai.org/proceedings/1997/123 ER -Copied
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