Data Mining Evolutionary Learning (DMEL) using H base
Miss. Mansi Shah, Ms. Seema Kolkur "Data Mining Evolutionary Learning (DMEL) using H base". International Journal of Computer Trends and Technology (IJCTT) V33(2):60-64, March 2016. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.
Abstract -
In current market scenarios, telecom
companies are quite competitive and look forward to
have lion’s share in the market by winning new and
withholding existing customers. Customers who are
lost to competitor are known as Churned customers
and can be retain by adopting Churn prevention
model. For a given dataset, this model predicts the
list of customers to be churned in future enabling the
respective authorities to take action accordingly.
However in telecom, the results of algorithms suffer
due to disproportion nature and vast size of datasets.
In this paper, Genetic Programming (GP) based
approach for modelling the challenging problem of
churn prediction is incorporated in HBASE. A data
mining algorithm, Data Mining Evolutionary
Learnings (DMEL), handles a classification problem
which helps to meet accuracy of prediction. As data
in telecom industry is going to increase so to make
the classification process fast DMEL algorithm is
incorporated in HBase. For competitive telecom
industry, churn prediction approach would be
significantly beneficial.
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Keywords
telecom industry, churn prediction,
genetic algorithms, DMEL, HBase.