A Comprehensive Approach to Behavioral Data Analysis and Machine Learning within Unified Systems

Ashish Hota

No rjpxs, OSF Preprints from Center for Open Science

Abstract: The integration of behavioral data analysis and machine learning (ML) within unified systems has become increasingly vital for enhanced decision-making and system optimization across various industries, including healthcare, marketing, and finance. Behavioral data—comprising user actions, preferences, and interactions—provides valuable insights into emerging trends, enabling adaptive and intelligent system functionalities. Coupling this with ML allows systems to continuously learn and improve their performance. This paper presents a comprehensive approach to integrating behavioral data analysis and ML within unified systems, covering key methodologies, technical challenges, applications, and a roadmap for future developments. Additionally, the article includes technical facts, tables, diagrams, and comparisons to aid in understanding the technical aspects and advantages of this integration.

Date: 2024-12-16
New Economics Papers: this item is included in nep-cmp
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Persistent link: https://EconPapers.repec.org/RePEc:osf:osfxxx:rjpxs

DOI: 10.31219/osf.io/rjpxs

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