Searching for Interacting Features
Proceedings of the Twentieth International Joint Conference on Artificial Intelligence. Pages 1156-1160.
Abstract
Feature interaction presents a challenge to feature selection for classification. A feature by itself may have little correlation with the target concept, but when it is combined with some other features, they can be strongly correlated with the target concept. Unintentional removal of these features can result in poor classification performance. Handling feature interaction can be computationally intractable. Recognizing the presence of feature interaction, we propose to efficiently handle feature interaction to achieve efficient feature selection and present extensive experimental results of evaluation.
@inproceedings{ijcai2007p187,
title = {Searching for Interacting Features},
author = {Zhao, Zheng and Liu, Huan},
booktitle = {Proceedings of the Twentieth International Joint Conference on
Artificial Intelligence, {IJCAI-07}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Ramon López de Mántaras},
pages = {1156--1160},
year = {2007},
url = {https://ijcai.org/proceedings/2007/187},
}
TY - CPAPER TI - Searching for Interacting Features AU - Zhao, Zheng AU - Liu, Huan T2 - Proceedings of the Twentieth International Joint Conference on Artificial Intelligence, IJCAI-07 PB - International Joint Conferences on Artificial Intelligence PY - 2007 SP - 1156 EP - 1160 UR - https://ijcai.org/proceedings/2007/187 ER -Copied
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