A review of data mining algorithms on Hadoop's MapReduce

Sikha Bagui and Sean Spratlin

International Journal of Data Science, 2018, vol. 3, issue 2, 146-169

Abstract: This paper is a review of the most frequently used data mining algorithms on Hadoop's MapReduce. We describe the algorithms with respect to their implementation and performance on Hadoop's MapReduce. We also discuss the similarities and differences between MapReduce's parallel or distributed implementations and the original standard sequential implementations.

Keywords: Hadoop; MapReduce; Classification; Clustering; KNN; SVM; Regression; Association Rule Mining. (search for similar items in EconPapers)
Date: 2018
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.inderscience.com/link.php?id=92285 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ids:ijdsci:v:3:y:2018:i:2:p:146-169

Access Statistics for this article

More articles in International Journal of Data Science from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().