Journal article
Oblique Multicategory Decision Trees Using Nonlinear Programming
INFORMS journal on computing, Vol.17(1), pp.25-31
01/01/2005
DOI: 10.1287/ijoc.1030.0047
Abstract
Induction of decision trees is a popular and effective method for solving classification problems in data-mining applications. This paper presents a new algorithm for multi-category decision tree induction based on nonlinear programming. This algorithm, termed OC-SEP (Oblique Category SEParation), combines the advantages of several other methods and shows improved generalization performance on a collection of real-world data sets.
Details
- Title: Subtitle
- Oblique Multicategory Decision Trees Using Nonlinear Programming
- Creators
- W. Nick Street - University of Iowa
- Resource Type
- Journal article
- Publication Details
- INFORMS journal on computing, Vol.17(1), pp.25-31
- DOI
- 10.1287/ijoc.1030.0047
- ISSN
- 1091-9856
- eISSN
- 1526-5528
- Language
- English
- Date published
- 01/01/2005
- Academic Unit
- Bus Admin College; Nursing; Computer Science; Business Analytics
- Record Identifier
- 9984380422502771
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