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).

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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.

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), Inspec (IET), Google Scholar, Crossref, ProQuest, Electronic Journals Library.
  • E-mail: ijmlc@ejournal.net