NDLI: A comparative analysis of data sets using Machine Learning techniques

Content Provider	IEEE Xplore Digital Library
Author	Abhilash, C.B. Rohitaksha, K. Biradar, S.
Copyright Year	2014
Description	Author affiliation: Comput. Sci. & Eng., Angadi Inst. of Technol. & Manage., Belgaum, India (Biradar, S.) \|\| Comput. Sci. & Eng., JSS Acad. of Tech. Educ., Bangalore, India (Abhilash, C.B.; Rohitaksha, K.)
Abstract	Machine Learning techniques are most widely used in the field of clustering of data. The K-means algorithm is one which is widely used algorithm for clustering of data sets and is easy to understand and simulate on different datasets. In our paper work we have used K-means algorithm for clustering of yeast dataset and iris datasets, in which clustering resulted in less accuracy with more number of iterations. We are simulating an improved version in K- means algorithm for clustering of these datasets, the Improved K-means algorithm use the technique of minimum spanning tree. An undirected graph is generated for all the input data points and then shortest distance is calculated which intern results in better accuracy and also with less number of iterations. Both algorithms have been simulated using java programming language; the results obtained from both algorithms are been compared and analyzed. Algorithms have been run for several times under different clustering groups and the analysis results showed that the Improved K- means algorithm has provided a better performance as compared to K-means algorithm; also Improved K-means algorithm showed that, as the number of cluster values increases the accuracy of the algorithm also increases. Also we have inferred from the results that at a particular value of K (cluster groups) the accuracy of Improved K-means algorithm is optimal.
Sponsorship	IEEE India Counc. C Chapt.
Starting Page	24
Ending Page	29
File Size	606275
Page Count	6
File Format	PDF
e-ISBN	9781479925728
DOI	10.1109/IAdCC.2014.6779289
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-02-21
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis Iris Accuracy Improved K-Means K-Means Clustering algorithms Genomics iris dataset Yeast dataset Bioinformatics MST
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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