Leveraging PyCaret for Classification Tasks in Banking Industry: A Comparative Study

Karthika Gopalakrishnan

Abstract: Classification problems in the banking industry, such as credit risk assessment and fraud detection, demand robust and efficient solutions. PyCaret, an open - source Python library, offers a comprehensive toolkit for automating machine learning tasks. In this paper, we explore the capabilities of PyCaret in addressing classification challenges in banking. We provide an overview of PyCaret, review relevant literature, discuss its supported models, and demonstrate its application in banking classification tasks. Through practical examples, the paper illustrates PyCaret's efficacy, ease of use, and efficiency in solving real - world banking problems.

Keywords: PyCaret, Classification, Banking Industry, Credit Risk Assessment, Fraud Detection, Machine Learning Automation

How to Cite?: Karthika Gopalakrishnan, "Leveraging PyCaret for Classification Tasks in Banking Industry: A Comparative Study", Volume 11 Issue 12, December 2022, International Journal of Science and Research (IJSR), Pages: 1346-1352, https://www.ijsr.net/getabstract.php?paperid=SR24628181058, DOI: https://dx.doi.org/10.21275/SR24628181058