Oblique multicategory decision trees using nonlinear programming

Oblique multicategory decision trees using nonlinear programming

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Article ID: iaor2007442
Country: United States
Volume: 17
Issue: 1
Start Page Number: 25
End Page Number: 31
Publication Date: Dec 2005
Journal: INFORMS Journal On Computing
Authors:
Keywords: artificial intelligence
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.

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