NDLI: Improved Research to K-means Initial Cluster Centers

Content Provider	IEEE Xplore Digital Library
Author	Zhang Min Duan Kai-fei
Copyright Year	2015
Description	Author affiliation: Coll. of Inf. & Eng., Dalian Univ., Dalian, China (Zhang Min; Duan Kai-fei)
Abstract	K-means in the field of clustering analysis algorithms is a kind of more traditional algorithm. It exists many shortcomings. For example, K value is easily affected by man-made subjective factors, and the algorithm is easy to fall into a local optimal solution, and the clustering result is not stable, etc, And K-means++ algorithm as the classic improved algorithm of K-means algorithm, but there is still a phenomenon of unstable cluster center. This paper is a kind of improvement aimed at the shortcoming of K-means++ algorithm, which introduces the concept of the variance in probability and mathematical statistics. Variance reflects the degree of density between samples and other samples. In the K-means++ algorithm when you select the first initial clustering center, you need to select minimum variance of sample points, which is in the position of the largest sample density, then you select the next cluster centers based on the weight method of $D^{2}$ which is described in the K-means++ algorithm. Experimental results show the accuracy is higher and stability is better.
Starting Page	349
Ending Page	353
File Size	161534
Page Count	5
File Format	PDF
e-ISBN	9781467392952
DOI	10.1109/FCST.2015.61
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-08-26
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis Iris K-means++ algorithm Accuracy Machine learning algorithms initial cluster centers variance Clustering algorithms Data collection Probability clustering
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
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Mr. Siddhartha Mukherjee siddhartha@ndl.gov.in
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
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	ndl-support@iitkgp.ac.in
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9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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