DMCA
Automatic Construction of Decision Trees from Data: A Multi-Disciplinary Survey (1997)
Cached
Download Links
- [www.itlabs.umn.edu]
- [www.cs.uiuc.edu]
- [www.cs.jhu.edu]
- DBLP
Other Repositories/Bibliography
| Venue: | Data Mining and Knowledge Discovery |
| Citations: | 224 - 1 self |
BibTeX
@ARTICLE{Murthy97automaticconstruction,
author = {Sreerama K. Murthy},
title = {Automatic Construction of Decision Trees from Data: A Multi-Disciplinary Survey},
journal = {Data Mining and Knowledge Discovery},
year = {1997},
volume = {2},
pages = {345--389}
}
Share
 |
 |
 |
 |
||
OpenURL
Abstract
Decision trees have proved to be valuable tools for the description, classification and generalization of data. Work on constructing decision trees from data exists in multiple disciplines such as statistics, pattern recognition, decision theory, signal processing, machine learning and artificial neural networks. Researchers in these disciplines, sometimes working on quite different problems, identified similar issues and heuristics for decision tree construction. This paper surveys existing work on decision tree construction, attempting to identify the important issues involved, directions the work has taken and the current state of the art. Keywords: classification, tree-structured classifiers, data compaction 1. Introduction Advances in data collection methods, storage and processing technology are providing a unique challenge and opportunity for automated data exploration techniques. Enormous amounts of data are being collected daily from major scientific projects e.g., Human Genome...
Keyphrases
decision tree multi-disciplinary survey automatic construction decision tree construction tree-structured classifier similar issue data compaction unique challenge processing technology multiple discipline decision theory data exploration technique valuable tool artificial neural network data exists signal processing different problem enormous amount pattern recognition important issue current state machine learning data collection method human genome major scientific project introduction advance
