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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 |
Files in This Item:
File | Description | Size | Format | |
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PREDICT CUSTOMER CHURN THROUGH CLASS IMBALANCE WITH MODIFIED RIPPER ALGORTHIM.docx | 10.2 kB | Microsoft Word XML | View/Open |
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