Please use this identifier to cite or link to this item:
http://localhost:8080/xmlui/handle/123456789/1626Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Nijhawan, Vani Kapoor | - |
| dc.contributor.author | Madan, Mamta | - |
| dc.contributor.author | Dave, Meenu | - |
| dc.date.accessioned | 2025-03-10T06:11:12Z | - |
| dc.date.available | 2025-03-10T06:11:12Z | - |
| dc.date.issued | 2019-05 | - |
| dc.identifier.uri | http://localhost:8080/xmlui/handle/123456789/1626 | - |
| dc.description.abstract | With the availability of numerous data, in each and every sphere, it has become significant to analyze the voluminous data, and utilize the generated patterns for the future predictions. This is what we refer to as data mining. This paper exploits, decision tree technique, to predict churning trends of telecom users. For this study, authors are making use of R and its GUI Rattle.In this paper, the focus is, to compare the variations in churning patterns of a number of users, based on the reflections made by different variables or factors and then make the predictions thereafter. | en_US |
| dc.language.iso | en | en_US |
| dc.subject | Data mining, Decision Tree, Customer churn, RStudio, Rattle | en_US |
| dc.title | A Comparative Analysis Using RStudio for Churn Predition | en_US |
| dc.type | Article | en_US |
| Appears in Collections: | VSIT | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| A Comparative Analysis Using RStudio for Churn Predition.pdf | 609.94 kB | Adobe PDF | View/Open |
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