Volume & Issue no: Volume 6, Issue 2, March - April 2017
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Title: |
Enhancing Clustering Mechanism by Implementation of EM Algorithm for Gaussian Mixture Model
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Author Name: |
Jyoti, Dr. Rajendar Singh Chhillar |
Abstract: |
Abstract: Big data[1] is a term for data sets that are so big or
complex that traditional data processing applications are
inadequate. Challenges include analysis, data curtain, search,
sharing, storage, transfer, visualization, querying &
information privacy. term often refers simply to use of
predictive analytics or certain other advanced methods to
extract value from data, & seldom to a particular size of data
set. Accuracy in big data might lead to more confident decision
making, & better decisions could result in greater operational
efficiency, cost reduction & reduced risk. Data mining[7] is
central step in a process called knowledge discovery in
databases, namely step in which modeling techniques are
include. Research areas like artificial intelligence, machine
learning, & soft computing had contributed to its arsenal of
methods. In our opinion fuzzy approaches could play an
important role in data mining, because they given
comprehensible results (although this goal is maybe because
this is sometimes hard to achieve within other methods).
Keywords—Data mining, web mining, web intelligence,
knowledge discovery, fuzzy logic, K-mean |
Cite this article: |
Jyoti, Dr. Rajendar Singh Chhillar , "
Enhancing Clustering Mechanism by Implementation of EM Algorithm for Gaussian Mixture Model
" , International Journal of Emerging Trends & Technology in Computer Science (IJETTCS) ,
Volume 6, Issue 2, March - April 2017 , pp.
155-158 , ISSN 2278-6856.
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