@inproceedings{441ea60fc5184e5baf83bdb54f7e1b32,
title = "Building simple models: A case study with decision trees",
abstract = "Building correctly-sized models is a central challenge for induction algorithms. Many approaches to decision tree induction fail this challenge. Under a broad range of circumstances, these approaches exhibit a nearly linear relationship between training set size and tree size, even after accuracy has ceased to increase. These algorithms fail to adjust for the statistical effects of comparing multiple subtrees. Adjusting for these effects produces trees with little or no excess structure.",
author = "David Jensen and Tim Oates and Cohen, {Paul R.}",
note = "Publisher Copyright: {\textcopyright} Springer-Verlag Berlin Heidelberg 1997.; 2nd International Symposium on Intelligent Data Analysis, IDA 1997 ; Conference date: 04-08-1997 Through 06-08-1997",
year = "1997",
doi = "10.1007/bfb0052842",
language = "English (US)",
isbn = "9783540633464",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer-Verlag",
pages = "211--222",
editor = "Xiaohui Liu and Paul Cohen and Michael Berthold",
booktitle = "Advances in Intelligent Data Analysis",
}