Constructive Induction Using a Non-Greedy Strategy for Feature Selection
Abstract
We present a method for feature construction and selection that finds a minimal set of conjunctive features that are appropriate to perform the classification task. For problems where this bias is appropriate, the method outperforms other constructive induction algorithms and is able to achieve higher classification accuracy. The application of the method in the search for minimal multi-level boolean expressions is presented and analyzed with the help of some examples.
Cite
Text
Oliveira and Sangiovanni-Vincentelli. "Constructive Induction Using a Non-Greedy Strategy for Feature Selection." International Conference on Machine Learning, 1992. doi:10.1016/B978-1-55860-247-2.50050-4Markdown
[Oliveira and Sangiovanni-Vincentelli. "Constructive Induction Using a Non-Greedy Strategy for Feature Selection." International Conference on Machine Learning, 1992.](https://mlanthology.org/icml/1992/oliveira1992icml-constructive/) doi:10.1016/B978-1-55860-247-2.50050-4BibTeX
@inproceedings{oliveira1992icml-constructive,
title = {{Constructive Induction Using a Non-Greedy Strategy for Feature Selection}},
author = {Oliveira, Arlindo L. and Sangiovanni-Vincentelli, Alberto L.},
booktitle = {International Conference on Machine Learning},
year = {1992},
pages = {355-360},
doi = {10.1016/B978-1-55860-247-2.50050-4},
url = {https://mlanthology.org/icml/1992/oliveira1992icml-constructive/}
}