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Author Bshouty, Nader H. ♦ Goldman, Sally A. ♦ Mathias, H. David ♦ Suri, Subhash ♦ Tamaki, Hisao
Source ACM Digital Library
Content type Text
Publisher Association for Computing Machinery (ACM)
File Format PDF
Copyright Year ©1998
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Computational learning ♦ Geometric concepts
Abstract We present an efficient algorithm for PAC-learning a very general class of geometric concepts over R consistent with a given set of labeled examples. We also present a statistical query version of our algorithm that can tolerate random classification noise. Finally we present a generalization of the standard ε-net result of Haussler and Welzl [1987] and apply it to give an alternative noise-tolerant algorithm for $\textit{d}$ = 2 based on geometric subdivisions.
ISSN 00045411
Age Range 18 to 22 years ♦ above 22 year
Educational Use Research
Education Level UG and PG
Learning Resource Type Article
Publisher Date 1998-09-01
Publisher Place New York
e-ISSN 1557735X
Journal Journal of the ACM (JACM)
Volume Number 45
Issue Number 5
Page Count 28
Starting Page 863
Ending Page 890


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Source: ACM Digital Library