Message Length as an Effective Ockham’s Razor in Decision Tree Induction
Abstract
The validity of the Ockham’s Razor principle is a topic of much debate. A series of empirical investigations have sought to discredit the principle by the application of decision trees to learning tasks using node cardinality as the objective function. As a response to these papers, we suggest that the message length of a hypothesis can be used as an effective interpretation of Ockham’s Razor, resulting in positive empirical support for the principle. The theoretical justification for this Bayesian interpretation is also investigated.
Cite
Text
Needham and Dowe. "Message Length as an Effective Ockham’s Razor in Decision Tree Induction." Proceedings of the Eighth International Workshop on Artificial Intelligence and Statistics, 2001.Markdown
[Needham and Dowe. "Message Length as an Effective Ockham’s Razor in Decision Tree Induction." Proceedings of the Eighth International Workshop on Artificial Intelligence and Statistics, 2001.](https://mlanthology.org/aistats/2001/needham2001aistats-message/)BibTeX
@inproceedings{needham2001aistats-message,
title = {{Message Length as an Effective Ockham’s Razor in Decision Tree Induction}},
author = {Needham, Scott and Dowe, David L.},
booktitle = {Proceedings of the Eighth International Workshop on Artificial Intelligence and Statistics},
year = {2001},
pages = {216-223},
volume = {R3},
url = {https://mlanthology.org/aistats/2001/needham2001aistats-message/}
}