A machine learning approach to identify potential customer

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DC Field	Value	Language
dc.contributor.author	Choudhury, A.	-
dc.contributor.author	Nur, Kamruddin	-
dc.date.accessioned	2022-01-10T13:56:12Z	-
dc.date.available	2022-01-10T13:56:12Z	-
dc.date.issued	2019-01	-
dc.identifier.issn	10.1109/ICREST.2019.8644458	-
dc.identifier.uri	http://dspace.aiub.edu:8080/jspui/handle/123456789/241	-
dc.description.abstract	To lift the revenue boundary and stay ahead of the competitors it is important to understand customer's purchase behavior. Different business industries proposed different policies to explore the potentiality of a customer based on statistical analysis. In this paper, we rather propose a machine learning approach to identify potential customers for a retail superstore. The paper proposed an engineered approach to classify potential customer, based on previously recorded purchase behavior. Using this classification as ground truth, we then apply machine learning algorithms to find a pattern to predict potential customers with an accuracy of 99.4%.	en_US
dc.publisher	IEEE	en_US
dc.subject	Machine Learning	en_US
dc.subject	Purchase Behaviour Analysis	en_US
dc.subject	Customer Classificaton	en_US
dc.title	A machine learning approach to identify potential customer	en_US
dc.type	Article	en_US
Appears in Collections:	Publications: Conference

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