The Decision List Machine
Abstract
We introduce a new learning algorithm for decision lists to allow features that are constructed from the data and to allow a trade- ofi between accuracy and complexity. We bound its generalization error in terms of the number of errors and the size of the classifler it flnds on the training data. We also compare its performance on some natural data sets with the set covering machine and the support vector machine.
Cite
Text
Sokolova et al. "The Decision List Machine." Neural Information Processing Systems, 2002.Markdown
[Sokolova et al. "The Decision List Machine." Neural Information Processing Systems, 2002.](https://mlanthology.org/neurips/2002/sokolova2002neurips-decision/)BibTeX
@inproceedings{sokolova2002neurips-decision,
title = {{The Decision List Machine}},
author = {Sokolova, Marina and Marchand, Mario and Japkowicz, Nathalie and Shawe-taylor, John S.},
booktitle = {Neural Information Processing Systems},
year = {2002},
pages = {945-952},
url = {https://mlanthology.org/neurips/2002/sokolova2002neurips-decision/}
}