A Novel Hybridization of Expectation-Maximization and K-Means Algorithms for Better Clustering Performance

E-ISSN： 1941-6245|7|2|47-74

ISSN： 1941-6237

Source： International Journal of Ambient Computing and Intelligence (IJACI), Vol.7, Iss.2, 2016-07, pp. : 47-74

Disclaimer: Any content in publications that violate the sovereignty, the constitution or regulations of the PRC is not accepted or approved by CNPIEC.

Previous Menu Next

Abstract

Related content

A Novel Hybridization of ARIMA, ANN, and K-Means for Time Series Forecasting

International Journal of Knowledge and Systems Science (IJKSS), Vol. 8, Iss. 4, 2017-10 ,pp. : 30-53

IGI Global_journal

Access to resources Recommend Favorite

Speed-up for the expectation-maximization algorithm for clustering categorical data

By Jollois F. Nadif M.

Journal of Global Optimization, Vol. 37, Iss. 4, 2007-04 ,pp. : 513-525

Springer Publishing Company

Access to resources Recommend Favorite

A novel unsupervised classification approach for network anomaly detection by k-Means clustering and ID3 decision tree learning methods

By Yasami Yasser Mozaffari Saadat

The Journal of Supercomputing, Vol. 53, Iss. 1, 2010-07 ,pp. : 231-245

Springer Publishing Company

Access to resources Recommend Favorite

A High Performance Model for Task Allocation in Distributed Computing System Using K-Means Clustering Technique

International Journal of Distributed Systems and Technologies (IJDST), Vol. 9, Iss. 3, 2018-07 ,pp. : 1-23

IGI Global_journal

Access to resources Recommend Favorite

ABK-means: an algorithm for data clustering using ABC and K-means algorithm

By Krishnamoorthi M. Natarajan A.M.

International Journal of Computational Science and Engineering, Vol. 8, Iss. 4, 2013-10 ,pp. : 383-391

Inderscience Publishers

Access to resources Recommend Favorite