Journal of Mathematical Problems, Equations and Statistics
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P-ISSN: 2709-9393, E-ISSN: 2709-9407

2023, Vol. 4, Issue 2, Part A


Integrating statistical methods with AI for enhanced predictive modeling


Author(s): KVS Naga Lakshmi and Kuparala Venkata Vidyasagar

Abstract: The integration of advanced statistical methods with artificial intelligence (AI) techniques presents a novel approach to predictive modeling. This research article discusses a system that combines the interpretability of traditional statistical methods with the adaptive learning capabilities of AI. We provide a comprehensive framework that enhances predictive accuracy, reliability, and interpretability. This hybrid approach is applicable across various domains, including healthcare, finance, marketing, and environmental science. The system addresses limitations of both paradigms when used in isolation and includes robust validation protocols, ethical AI practices, and user-friendly interfaces. We demonstrate the system’s efficacy through case studies and discuss its potential impact on data-driven decision-making across industries.

Pages: 86-97 | Views: 394 | Downloads: 248

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Journal of Mathematical Problems, Equations and Statistics
How to cite this article:
KVS Naga Lakshmi and Kuparala Venkata Vidyasagar. Integrating statistical methods with AI for enhanced predictive modeling. Journal of Mathematical Problems, Equations and Statistics. 2023; 4(2): 86-97.
Journal of Mathematical Problems, Equations and Statistics
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