PREDICT CUSTOMER CHURN THROUGH CLASS IMBALANCE WITH MODIFIED RIPPER ALGORTHIM

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DC Field	Value	Language
dc.contributor.author	M, Rajeswari	-
dc.contributor.author	S, Deepika	-
dc.date.accessioned	2020-06-17T10:20:27Z	-
dc.date.available	2020-06-17T10:20:27Z	-
dc.date.issued	2018-12	-
dc.identifier.issn	Online:2349-9761	-
dc.identifier.issn	Print:2249-0191	-
dc.identifier.uri	http://localhost:8080/xmlui/handle/123456789/205	-
dc.description.abstract	Competitive advantage is gained by firm through new areas such as data warehousing, data mining and campaign management software have made Customer Relationship Management(CRM). This research aims to develop methodologies for predicting customer churn in advance, while keeping misclassification rates to a minimum.	en_US
dc.language.iso	en	en_US
dc.publisher	Speak Foundation-International Journal of Management and Social Sciences(IJMSS)	en_US
dc.subject	Churn	en_US
dc.subject	Class Imbalance	en_US
dc.subject	Customer Relationship Management	en_US
dc.subject	Data Mining	en_US
dc.title	PREDICT CUSTOMER CHURN THROUGH CLASS IMBALANCE WITH MODIFIED RIPPER ALGORTHIM	en_US
dc.type	Article	en_US
Appears in Collections:	International Journals

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