Improved Classification Approach for Business Intelligence‎Using Data Specific and Feature Oriented Min-Max Normalization

  • Authors

    • Syed Ziaur Rahman University of South Florida, United States
    • Bhuvan Unhelkar University of South Florida, United States
    • Prasun Chakrabarti Department of Computer Science and Engineering, Sir Padampat Singhania University, Udaipur Rajasthan, India
    • Mohammed Ali Hussain Professor of CSE and Dean R & D, Sreenidhi Institute of Science and Technology, Hyderabad, India
    https://doi.org/10.14419/npfq8f76

    Received date: July 27, 2025

    Accepted date: September 2, 2025

    Published date: September 19, 2025

  • Business Intelligence; Management Dashboards; Machine Learning; Min-Max Normalization; Classification Methods

  • Abstract

    Business intelligence is becoming more and more important to managers in today's corporate setting as a crucial aspect of information ‎technology. Many companies are eager to use intelligent technologies to enhance their decision-making processes in corporate operations. ‎Accordingly, intelligence is typically linked to human-like traits, including the ability to assimilate new information, learn from mistakes, and ‎pursue objectives similar to those of a human. One of the main objectives of business intelligence integration across businesses is to ‎generate reports through management dashboards that use key indicators to facilitate informed decision-making. The objective of this paper is to ‎develop a practical model that uses machine learning indicators and algorithms to optimize the product sales system using classification ‎techniques. Several factors are used by the model to enhance client classification techniques. Additionally, the study uses association rules to ‎look at clients' shopping carts, find links between the items they have bought, and generate personalized offers based on the rules they have ‎discovered. Different classification techniques, including C4.5, random forest, and reduced error pruning tree, are used to compare with the ‎suggested methodology before being used to evaluate and improve the results. The findings show that the best results should be obtained ‎using the recommended methodology in conjunction with the indicated model‎.

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    Rahman , S. Z. ., Unhelkar , B. ., Chakrabarti , P. ., & Hussain, M. A. . (2025). Improved Classification Approach for Business Intelligence‎Using Data Specific and Feature Oriented Min-Max Normalization. International Journal of Basic and Applied Sciences, 14(5), 700-713. https://doi.org/10.14419/npfq8f76