PREDICT CUSTOMER CHURN THROUGH CLASS IMBALANCE WITH MODIFIED RIPPER ALGORTHIM

Please use this identifier to cite or link to this item: http://localhost:8080/xmlui/handle/123456789/205

Title:	PREDICT CUSTOMER CHURN THROUGH CLASS IMBALANCE WITH MODIFIED RIPPER ALGORTHIM
Authors:	M, Rajeswari S, Deepika
Keywords:	Churn Class Imbalance Customer Relationship Management Data Mining
Issue Date:	Dec-2018
Publisher:	Speak Foundation-International Journal of Management and Social Sciences(IJMSS)
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.
URI:	http://localhost:8080/xmlui/handle/123456789/205
ISSN:	Online:2349-9761 Print:2249-0191
Appears in Collections:	International Journals

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