PREDICT CUSTOMER CHURN THROUGH CLASS IMBALANCE WITH MODIFIED RIPPER ALGORTHIM

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dc.contributor.authorM, Rajeswari
dc.contributor.authorS, Deepika
dc.date.accessioned2020-06-17T10:20:27Z
dc.date.available2020-06-17T10:20:27Z
dc.date.issued2018-12
dc.description.abstractCompetitive 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.identifier.issnOnline:2349-9761
dc.identifier.issnPrint:2249-0191
dc.identifier.urihttps://dspace.psgrkcw.com/handle/123456789/205
dc.language.isoenen_US
dc.publisherSpeak Foundation-International Journal of Management and Social Sciences(IJMSS)en_US
dc.subjectChurnen_US
dc.subjectClass Imbalanceen_US
dc.subjectCustomer Relationship Managementen_US
dc.subjectData Miningen_US
dc.titlePREDICT CUSTOMER CHURN THROUGH CLASS IMBALANCE WITH MODIFIED RIPPER ALGORTHIMen_US
dc.typeArticleen_US

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