Two-Stage Constructing Hyper-Plane for Each Test Node of Decision Tree

Abstract:

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How to construct the “appropriate” split hyper-plane in test nodes is the key of building decision trees. Unlike a univariate decision tree, a multivariate (oblique) decision tree could find the hyper-plane that is not orthogonal to the features’ axes. In this paper, we re-explain the process of building test nodes in terms of geometry. Based on this, we propose a method of learning the hyper-plane with two stages. The tree (TSDT) induced in this way keeps the interpretability of univariate decision trees and the trait of multivariate decision trees which could find oblique hyper-plane. The tests of the impact of Combination methods tell us that TSDT based combination algorithm is much better than other tree based combination methods in accuracy.

Info:

Periodical:

Edited by:

Zhenyu Du and Bin Liu

Pages:

776-779

DOI:

10.4028/www.scientific.net/AMM.26-28.776

Citation:

W. She et al., "Two-Stage Constructing Hyper-Plane for Each Test Node of Decision Tree", Applied Mechanics and Materials, Vols. 26-28, pp. 776-779, 2010

Online since:

June 2010

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Price:

$35.00

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