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General Information
    • ISSN: 2010-3700 (Online)
    • Abbreviated Title: Int. J. Mach. Learn. Comput.
    • Frequency: Bimonthly
    • DOI: 10.18178/IJMLC
    • Editor-in-Chief: Dr. Lin Huang
    • Executive Editor:  Ms. Cherry L. Chen
    • Abstracing/Indexing: Scopus (since 2017), EI (INSPEC, IET), Google Scholar, Crossref, ProQuest, Electronic Journals Library.
    • E-mail: ijmlc@ejournal.net
Dr. Lin Huang
Metropolitan State University of Denver, USA
It's my honor to take on the position of editor in chief of IJMLC. We encourage authors to submit papers concerning any branch of machine learning and computing.

IJMLC 2011 Vol.1(2): 213-217 ISSN: 2010-3700
DOI: 10.7763/IJMLC.2011.V1.31

‘Entropy’ on Covers and Its Application on Decision Tree Construction

Zhimin Wang
Abstract—Decision tree is a popular classification tool. To automatically construct a good decision tree, people have introduced entropy as a heuristic for attribute selection to deal with the intractable nature of finding an optimal solution with regard to the size of a tree. To solve a special kind of decision tree construction used in biological taxonomy, we need consider polymorphic attributes, against which a single instance may hold different values. To properly evaluate polymorphic attributes during tree construction, we propose the conditional form of a novel ‘entropy’ measure called ‘disconnectivity’ as the heuristic. In parallel to the theory of generalized entropy, ‘disconnectivity’ is also generalized to a family of measures.

Index Terms—cover, decision tree, entropy, polymorphic character

Zhimin Wang is with the Harvard University Herbaria, Cambridge, MA 02138 USA (phone: 617-495-1948; fax: 617-495-9484; e-mail: zhimin.wangzm@gmail.com).


Cite: Zhimin Wang, "‘Entropy’ on Covers and Its Application on Decision Tree Construction," International Journal of Machine Learning and Computing vol. 1, no. 2, pp. 213-217, 2011.

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