Churn Forecast Portal using Random Forest Classifier

Arpan, Chakraborty and Manjula Sanjay, Koti (2024) Churn Forecast Portal using Random Forest Classifier. Journal of Innovation and Technology, 2024 (44). pp. 1-7. ISSN 2805-5179

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Abstract

The competitive scene inside the telecom and keeping cash businesses demands compelling client upkeep strategies. This request almost centres on making a energetic Client Churn Figure system utilizing machine learning strategies, especially the Subjective Forest Classifier, to recognize atrisk clients proactively. By analysing client data, tallying socioeconomics, advantage utilization plans, and charging information, the system predicts the likelihood of churn. The encounters picked up coordinate companies in actualizing centred on trade to make strides client steadfastness. The made system is affirmed utilizing datasets from the telecom and overseeing an account division, outlining tall precision and unflinching quality in churn figure.

Item Type:	Article
Uncontrolled Keywords:	Customer Retention Strategies, Churn Prediction System, Machine Learning Techniques, Random Forest Classifier, Telecom and Banking Datasets
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science T Technology > T Technology (General) T Technology > TJ Mechanical engineering and machinery
Depositing User:	Unnamed user with email masilah.mansor@newinti.edu.my
Date Deposited:	12 Dec 2024 09:29
Last Modified:	12 Dec 2024 09:29
URI:	http://eprints.intimal.edu.my/id/eprint/2094

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