CUSTOMER STRESS PREDICTION IN TELECOM INDUSTRIES USING MACHINE LEARNING

Autor: V. Sriharsha, S. Giri Babu
Rok vydání: 2022
Zdroj: International Journal of Innovative Research in Engineering & Management. :219-222
ISSN: 2350-0557
DOI: 10.55524/ijirem.2022.9.5.31
Popis: In the competitive world especially in enterprises market maintaining valuable customers is becoming a difficult task. In one situation losing a customer is like decrease in profits for telecom industry growth, in another situation the cost of acquiring new customers is much higher than the cost of retaining the existing customers, for this critical situation the telecom industries should focus on retaining existing customers. This project will analyze the customer data which was collected as open dataset and predict the customer stress by applying supervised machine learning algorithms mainly using Linear Discriminant Analysis, Support Vector Machine, K Nearest Neighbor and Random Forest.
Databáze: OpenAIRE