Award Date
1-1-2005
Degree Type
Thesis
Degree Name
Master of Science (MS)
Department
Computer Science
First Committee Member
Kazem Taghva
Number of Pages
63
Abstract
Data mining represents the process of extracting interesting and previously unknown knowledge from data. In this thesis we address the important data mining problem of discovering association rules. An association rule expresses the dependence of a set of attribute-value pairs, also called items, upon another set of items; We also report on various implementation techniques for the well-known Apriori Algorithm and their time complexity.
Keywords
Algorithms; Analysis; Apriori; Data; Implementation; Mining
Controlled Subject
Computer science
File Format
File Size
1239.04 KB
Degree Grantor
University of Nevada, Las Vegas
Language
English
Permissions
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Repository Citation
Bondugula, Pavankumar, "Implementation and analysis of apriori algorithm for data mining" (2005). UNLV Retrospective Theses & Dissertations. 1927.
http://dx.doi.org/10.25669/3afg-dafe
Rights
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