摘要: This paper presents a new method (HOT) of generating oblique decision trees. Oblique trees have been shown to be useful tools for classification in some problem domains, producing accurate and intuitive solutions. The can incorporated into variety existing tree the illustrates this with two very distinct generators. key idea is learning vectors using corresponding families hyperplanes orthogonal these separate regions dominant classes. Experimental results indicate that learnt lead compact HOT simple easy incorporate most packages, yet its compare well much more complex schemes
sci-hub.se 参考文章(16)
Simon Kasif, Steven Salzberg, David G. Heath, Induction of Oblique Decision Trees. international joint conference on artificial intelligence. pp. 1002- 1007 ,(1993)
Wei-Yin Loh, Yu-Shan Shih, SPLIT SELECTION METHODS FOR CLASSIFICATION TREES ,(1997)
Aram Karalič, Employing linear regression in regression tree leaves european conference on artificial intelligence. pp. 440- 441 ,(1992)
Marcus Roland Frean, Small nets and short paths : optimising neural computation The University of Edinburgh. ,(1990)
W. D. Ray, Peter Young, Recursive Estimation and Time Series Analysis Journal of the Royal Statistical Society: Series A (General). ,vol. 149, pp. 280- 280 ,(1984) , 10.2307/2981573
Peter Young, Recursive Estimation and Time-Series Analysis: An Introduction ,(1984)
S. K. Murthy, S. Kasif, S. Salzberg, A system for induction of oblique decision trees Journal of Artificial Intelligence Research. ,vol. 2, pp. 1- 32 ,(1994) , 10.1613/JAIR.63
João Gama, Oblique Linear Tree intelligent data analysis. pp. 187- 198 ,(1997) , 10.1007/BFB0052840
Manish Mehta, Rakesh Agrawal, Jorma Rissanen, SLIQ: A fast scalable classifier for data mining Advances in Database Technology — EDBT '96. pp. 18- 32 ,(1996) , 10.1007/BFB0014141
Richard A Olshen, Charles J Stone, Leo Breiman, Jerome H Friedman, Classification and regression trees ,(1983)