Decision Tree Induction Based on Efficient Tree Restructuring
Abstract
The ability to restructure a decision tree efficiently enables a variety of approaches to decision tree induction that would otherwise be prohibitively expensive. Two such approaches are described here, one being incremental tree induction (ITI), and the other being non-incremental tree induction using a measure of tree quality instead of test quality (DMTI). These approaches and several variants offer new computational and classifier characteristics that lend themselves to particular applications.
Cite
Text
Utgoff et al. "Decision Tree Induction Based on Efficient Tree Restructuring." Machine Learning, 1997. doi:10.1023/A:1007413323501Markdown
[Utgoff et al. "Decision Tree Induction Based on Efficient Tree Restructuring." Machine Learning, 1997.](https://mlanthology.org/mlj/1997/utgoff1997mlj-decision/) doi:10.1023/A:1007413323501BibTeX
@article{utgoff1997mlj-decision,
title = {{Decision Tree Induction Based on Efficient Tree Restructuring}},
author = {Utgoff, Paul E. and Berkman, Neil C. and Clouse, Jeffery A.},
journal = {Machine Learning},
year = {1997},
pages = {5-44},
doi = {10.1023/A:1007413323501},
volume = {29},
url = {https://mlanthology.org/mlj/1997/utgoff1997mlj-decision/}
}