An Adaptive Hybrid Machine Learning Framework for Predictive Analytics
DOI:
https://doi.org/10.15680/IJCTECE.2026.0901015Keywords:
Adaptive Machine Learning, Hybrid Framework, Predictive Analytics, Ensemble Learning, Feature Selection, Model Optimization, Data-Driven Decision Making, Machine Learning IntegrationAbstract
Predictive analytics has become a critical component in data-driven decision-making across domains such as healthcare, finance, education, and e-commerce. Traditional machine learning models often face challenges related to data heterogeneity, dynamic patterns, and limited adaptability to changing environments. To address these issues, this research proposes an Adaptive Hybrid Machine Learning Framework designed to enhance prediction accuracy, robustness, and scalability. The framework integrates multiple learning paradigms, combining the strengths of supervised learning, ensemble techniques, and adaptive optimization strategies. It employs dynamic feature selection, hybrid model fusion, and continuous performance monitoring to automatically adjust model parameters based on data characteristics. Experimental evaluation conducted on benchmark datasets demonstrates that the proposed framework outperforms conventional single-model approaches in terms of accuracy, precision, recall, and computational efficiency. The results highlight the framework’s ability to handle complex, nonlinear data patterns while maintaining generalization capability. This study contributes to the field of predictive analytics by providing a flexible and intelligent architecture capable of delivering reliable predictions in real-world, evolving data environments.
References
[1]. Joshi, K., Joshi, N. K., Diwakar, M., Tripathi, A. N., & Gupta, H. (2019). Multi-focus image fusion using non-local mean filtering and stationary wavelet transform. International Journal of Innovative Technology and Exploring Engineering, 9(1), 344-350.
[2]. Pandey, N. K., Chaudhary, S., & Joshi, N. K. (2016, November). Resource allocation strategies used in cloud computing: A critical analysis. In 2016 2nd International Conference on Communication Control and Intelligent Systems (CCIS) (pp. 213-216). IEEE.
[3]. Joshi, K., Kirola, M., Chaudhary, S., Diwakar, M., & Joshi, N. K. (2019, March). Multi-focus image fusion using discrete wavelet transform method. In International conference on advances in engineering science management & technology (ICAESMT)-2019, Uttaranchal University, Dehradun, India.
[4]. Pandey, N. K., Chaudhary, S., & Joshi, N. K. (2017). Extended multi queue job scheduling in cloud. International Journal of Computer Science and Information Security (IJCSIS), 15(11), 1-8.
[5]. Joshi, K., Joshi, N. K., Diwakar, M., Gupta, H., & Baloni, D. (2020, February). Cross bilateral filter based image fusion in transform domain. In 5th International Conference on Next Generation Computing Technologies (NGCT-2019).
[6]. Harsh, O. K., & Joshi, N. K. (2008). Role of Technology on the Knowledge Management and Reuse. Communicated to Engineering Letters.
[7]. Pandey, N. K., & Joshi, N. K. (2018). Optimization of resource allocation strategy using modified PSO in cloud environment. International Journal of Computer Science and Information Security (IJCSIS), 16(3).
[8]. Bansal, Shonak, Sandeep Kumar, Arpit Jain, Vinita Rohilla, Krishna Prakash, Anupma Gupta, Tanweer Ali et al. "Design and TCAD analysis of few-layer graphene/ZnO nanowires heterojunction-based photodetector in UV spectral region." Scientific Reports 15, no. 1 (2025): 7762.
[9]. Jonnala, Naga Surekha, Renuka Chowdary Bheemana, Krishna Prakash, Shonak Bansal, Arpit Jain, Vaibhav Pandey, Mohammad Rashed Iqbal Faruque, and K. S. Al-Mugren. "DSIA U-Net: deep shallow interaction with attention mechanism UNet for remote sensing satellite images." Scientific Reports 15, no. 1 (2025): 549.
[10]. Jain, Arpit, Ashok Kumar, Mahadev, Jitendra Kumar Chaudhary, and Saurabh Singh. "Trust‐Based Reliability Scheme for Secure Data Sharing with Internet of Vehicles Networks." Internet Technology Letters 8, no. 2 (2025): e70000.
[11]. Kumar, Manish, Sandeep Yadav, Arpit Jain, Anita Singh, and Keshav Gupta. "Smog restoration of an image using oblique gradient profile." In AIP Conference Proceedings, vol. 3224, no. 1. AIP Publishing, 2025.
[12]. Mishra, V., Sharma, S., Jain, A., Gupta, K., & Jain, A. (2025, February). An exploration of clustering techniques for customer behaviour. In AIP Conference Proceedings (Vol. 3224, No. 1). AIP Publishing.
[13]. Jain, Trang, Arpit Jain, Rakesh Kumar Dwivedi, and Rakhi Saxena. "AI-Inspired Algorithm for the Automated Recognition of the World’s Oldest Script “Brahmi”." SN Computer Science 6, no. 1 (2024): 33.
[14]. Gowroju, Swathi, Shilpa Choudhary, Arpit Jain, and R. Srilakshmi. "Classification of Moderate and Advanced Dementia Patients Using Gradient Boosting Machine Technique: Classification of Moderate and Advanced Dementia Patients." In Revolutionizing AI with Brain-Inspired Technology: Neuromorphic Computing, pp. 261-288. IGI Global Scientific Publishing, 2025.
[15]. Chakravarty, A., Jain, A., & Saxena, A. K. (2024, November). Deep Learning Approach to Sugarcane Disease Identification: From Image Analysis to Mobile Application. In 2024 4th International Conference on Technological Advancements in Computational Sciences (ICTACS) (pp. 1696-1702). IEEE.
[16]. Goyal, Rohit, Krishan Kumar, Vivek Sharma, Rudramani Bhutia, Arpit Jain, and Munish Kumar. "Quantum-Inspired Optimization Algorithms for Scalable Machine Learning in Edge Computing." In 2024 4th International Conference on Technological Advancements in Computational Sciences (ICTACS), pp. 1888-1892. IEEE, 2024.
[17]. Gupta, G. K., Jain, A., Sharma, K., Kumar, P. A., Gupta, S., & Agarwal, S. (2024, September). A Novel Hybrid Framework for Energy-Efficient Clustering and Routing in Heterogeneous IoT-Driven Wireless Sensor Networks. In 2024 7th International Conference on Contemporary Computing and Informatics (IC3I) (Vol. 7, pp. 1125-1129). IEEE.
[18]. Kumar, S., Sharma, K., Kumar, P. A., Jain, A., Bhagat, S. K., & Singh, P. (2024, September). An Improved Particle Swarm Approach for Energy-Aware Location-Aided Routing in Mobile Ad-Hoc Network. In 2024 7th International Conference on Contemporary Computing and Informatics (IC3I) (Vol. 7, pp. 1119-1124). IEEE.
[19]. Srivastav, A., Agarwal, S., Jain, A., Tayal, S., Jain, S., & Sharma, K. (2024, September). Enhancing Blockchain Scalability: Innovative Solutions for Optimized Performance in Decentralized Networks. In 2024 7th International Conference on Contemporary Computing and Informatics (IC3I) (Vol. 7, pp. 1088-1094). IEEE.
[20]. Bisht, G. S., Jain, A., Bansla, V., Sharma, K., Bhutia, R., & Kumar, V. (2024, September). Enhanced Keypoint-Based Approach for Identifying Copy-Move Forgery in Digital Images. In 2024 7th International Conference on Contemporary Computing and Informatics (IC3I) (Vol. 7, pp. 1101-1106). IEEE.
[21]. Jain, A., Musunuri, A. S., Cheruku, S. R., Bhimanapati, V. B. R., Mahimkar, S., & Al-Farouni, M. H. (2024, August). Reinforcement Learning for Fake News Detection on Social Media with Blockchain Security. In 2024 4th International Conference on Blockchain Technology and Information Security (ICBCTIS) (pp. 320-325). IEEE.
[22]. Jain, A., Khatri, D. K., Ayyagiri, A., Mokkapati, C., Bhimanapati, V. B. R., & Alzubaidi, L. H. (2024, August). Secure and Scalable IoT Networks: Optimizing Blockchain and SDN for Smart Environments. In 2024 4th International Conference on Blockchain Technology and Information Security (ICBCTIS) (pp. 338-344). IEEE.
[23]. Agrawal, N. K., Priya, N., Sinha, P., Singh, P., Jain, A., & Kumar, M. (2024, May). Enhancing Data Aggregation Efficiency: Dynamic Energy-Aware Strategies in Wireless Sensor Networks. In 2023 International Conference on Smart Devices (ICSD) (pp. 1-5). IEEE.
[24]. Agrawal, N. K., Sharma, V., Singh, P., Sachi, S., Jain, A., & Alam, M. M. (2024, May). Fog Restoration in Hazy Images using Deep Transfer Learning. In 2023 International Conference on Smart Devices (ICSD) (pp. 1-5). IEEE.
[25]. Sachi, S., Jain, J., Jain, A., Patel, U. K., Bhatnagar, A., & Jain, A. (2024, May). Hy_PSO: Hybrid Algorithm for Lung Cancer Diagnosis and Prognosis. In 2023 International Conference on Smart Devices (ICSD) (pp. 1-5). IEEE.
[26]. Kolli, R. K., Eeti, S., Mahimkar, S., Chintha, V., Goel, P., & Jain, A. (2024, August). Securing WSN-IOT with Firefly Algorithm and Machine Learning for Intrusion Detection System. In 2024 1st International Conference on Advanced Computing and Emerging Technologies (ACET) (pp. 1-7). IEEE.
[27]. Kumar, V., Sen, C., Jain, A., Jain, A., & Sharma, A. (2024). Analysis of Business Intelligence in Healthcare Using Machine Learning. Optimized Predictive Models in Healthcare Using Machine Learning, 329-339.
[28]. Kumar, S., Ghai, D., Jain, A., Tripathi, S. L., & Rani, S. (Eds.). (2023). Multimodal Biometric and Machine Learning Technologies: Applications for Computer Vision. John Wiley & Sons.
[29]. Rao, K. B., Bhardwaj, Y., Rao, G. E., Gurrala, J., Jain, A., & Gupta, K. (2023, December). Early Lung Cancer Prediction by AI-Inspired Algorithm. In 2023 10th IEEE Uttar Pradesh Section International Conference on Electrical, Electronics and Computer Engineering (UPCON) (Vol. 10, pp. 1466-1469). IEEE.
[30]. Devi, S., Sharma, Y. K., Athithan, S., Sachi, S., Singh, A. K., & Jain, A. (2023, September). Implementation of ABC & WOA-Based Security Defense Mechanism for Distributed Denial of Service Attacks. In 2023 6th International Conference on Contemporary Computing and Informatics (IC3I) (Vol. 6, pp. 546-551). IEEE.
[31]. Singh, A. K., Jain, A., Sharma, Y. K., Athithan, S., & Sachi, S. (2023, September). Multi Objective Optimization Based Land Cover Classification Using NSGA-II. In 2023 6th International Conference on Contemporary Computing and Informatics (IC3I) (Vol. 6, pp. 552-556). IEEE.
[32]. Jain, A., Sharma, Y. K., Sachi, S., Athithan, S., & Singh, A. K. (2023, November). Fire Detection Using Image Processing Technique. In 2023 3rd International Conference on Technological Advancements in Computational Sciences (ICTACS) (pp. 873-877). IEEE.
[33]. Pandya, D., Pathak, R., Kumar, V., Jain, A., Jain, A., & Mursleen, M. (2023, May). Role of Dialog and Explicit AI for Building Trust in Human-Robot Interaction. In 2023 International Conference on Disruptive Technologies (ICDT) (pp. 745-749). IEEE.
