Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Harsh, Archit"'
Publikováno v:
International Journal of Computer Application, Vol.139 (3), pp.26-31, April, 2016
Outlier Detection is a critical and cardinal research task due its array of applications in variety of domains ranging from data mining, clustering, statistical analysis, fraud detection, network intrusion detection and diagnosis of diseases etc. Ove
Externí odkaz:
http://arxiv.org/abs/1803.04964
Publikováno v:
IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), December, 2015
In a multi-source environment, each source has its own credibility. If there is no external knowledge about credibility then we can use the information provided by the sources to assess their credibility. In this paper, we propose a way to measure co
Externí odkaz:
http://arxiv.org/abs/1803.04556
Autor:
Harsh, Archit
Publikováno v:
Theses and Dissertations.
A non-parametric data clustering technique for achieving efficient data-clustering and improving the number of clusters is presented in this thesis. K-Means and Expectation-Maximization algorithms have been widely deployed in data-clustering applicat
Externí odkaz:
https://scholarsjunction.msstate.edu/td/828
https://scholarsjunction.msstate.edu/cgi/viewcontent.cgi?article=1827&context=td
https://scholarsjunction.msstate.edu/cgi/viewcontent.cgi?article=1827&context=td
Publikováno v:
2015 IEEE 6th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP); 2015, p225-228, 4p