# Model for Predicting Customer Desertion of Telephony Service using Machine Learning

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/model-for-predicting-customer-desertion-of-telephony-service-using-machine/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Carlos Acero-Charaña,Erbert F. Osco Mamani,Tito Ale-Nieto |
| Citations | 4 |
| DOI | 10.14569/ijacsa.2021.0120320 |
| Fields | Business, Management and Accounting,Computer Science |
| Open Access | true |
| OA Status | diamond |
| OA URL | http://thesai.org/Downloads/Volume12No3/Paper_20-Model_for_Predicting_Customer_Desertion.pdf |
| OpenAlex ID | https://openalex.org/W3152204898 |
| Type | article |
| Year | 2021 |

## Paper authors

- [Erbert F. Osco Mamani](https://scholariq.org/researchers/erbert-f-osco-mamani/)

## Paper journal

- [International Journal of Advanced Computer Science and Applications](https://scholariq.org/journals/international-journal-of-advanced-computer-science-and-applications/)

## Paper primary topic

- [Customer churn and segmentation](https://scholariq.org/topics/customer-churn-and-segmentation/)

## Paper topics

- [Customer churn and segmentation](https://scholariq.org/topics/customer-churn-and-segmentation/)
- [Data Mining Algorithms and Applications](https://scholariq.org/topics/data-mining-algorithms-and-applications/)
- [Imbalanced Data Classification Techniques](https://scholariq.org/topics/imbalanced-data-classification-techniques/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.