A Generalized Study on Data Mining and Clustering Algorithms

Syed Thouheed Ahmed, S. Sreedhar Kumar, B. Anusha, P. Bhumika, M. Gunashree and B. Ishwarya
Additional contact information
Syed Thouheed Ahmed: Dr. T. Thimmaiah Institute of Technology, Department of Computer Science and Engineering
S. Sreedhar Kumar: Dr. T. Thimmaiah Institute of Technology, Department of Computer Science and Engineering
B. Anusha: Dr. T. Thimmaiah Institute of Technology, Department of Computer Science and Engineering
P. Bhumika: Dr. T. Thimmaiah Institute of Technology, Department of Computer Science and Engineering
M. Gunashree: Dr. T. Thimmaiah Institute of Technology, Department of Computer Science and Engineering
B. Ishwarya: Dr. T. Thimmaiah Institute of Technology, Department of Computer Science and Engineering

A chapter in New Trends in Computational Vision and Bio-inspired Computing, 2020, pp 1121-1129 from Springer

Abstract: Abstract Data Mining is the procedure of extracting information from a data set and transforms information into comprehensible structure for processing. Clustering is data mining technique used to process data elements into their related groups or partition. Thus, the process of partitioning data objects into subclasses is term as ‘cluster’. It consists of data objects with un-unified proposition of high inter similarity and low intra similarity ratios. Thus reflecting the quality of cluster depends on the methods used. Clustering also called data segmentation, divides huge data sets into several groups based upon their similarities. This paper discusses a literature study of various clustering techniques and their comparison on key issues to give guidance for choosing clustering algorithm for a specific research application. The comparison is based on computing performance and clustering accuracy.

Keywords: Data mining; Clustering; Partitioning; Segmentation (search for similar items in EconPapers)
Date: 2020
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

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:spr:sprchp:978-3-030-41862-5_114

Ordering information: This item can be ordered from
http://www.springer.com/9783030418625

DOI: 10.1007/978-3-030-41862-5_114

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().