Publication2021
A Proposed Model for Customer Churn Prediction and Factor Identification Behind Customer Churn in Telecom Industry
The record
- Type
- Publication
- Date
- 1 January 2021
- Level
- National
- Journal
- Lecture Notes in Electrical Engineering
- Volume
- 691
- Pages
- 359-369
- Published
- 1 January 2021
- DOI
- 10.1007/978-981-15-7511-2_34
- Scopus ID
- 85101570802
- ISSN
- 18761100
- Authors
- 4
- Open access
- No
- Citations
- 1
- International co-authorship
- No
- Co-author countries
- IN
Classification
Every label below carries the reasoning it was assigned on, the confidence band it was assigned in, and what produced it. The rubric is published.
UN Sustainable Development Goals
8 Promote sustained, inclusive and sustainable economic growth, full and productive employment and decent work for all
Customer churn prediction in telecom industry directly supports economic growth and business profitability through identifying retention factors and improving service competitiveness
- High confidence
- The subject matter is a strong and direct inference from the record type, the funding or organising body, or the programme context, even where the title alone is thin. Example: an ICMR-funded project against SDG 3, on the strength of the agency.
- Judged
- Judged against the published classification rubric, under the rubric and prompt versions recorded with the run that produced it.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
9.5 Enhance scientific research, upgrade technological capabilities, and increase researchers and R&D spending
Machine learning classification methodology using gradient boosting demonstrates research advancement in business intelligence and data mining applications
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
Viksit Bharat @2047
vb-2.3 Services and the knowledge economy
Telecom customer intelligence research supports services and knowledge economy through business analytics improving competitive positioning
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
Each label above carries the instrument and the version that produced it. How each classification is reached.
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- Source rows resolved into this record
- 1
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Citing this record
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KIIT Deemed to be University. “A Proposed Model for Customer Churn Prediction and Factor Identification Behind Customer Churn in Telecom Industry”. Kortex.