Enhancing Energy Efficiency and Classification Modeling Through a Combined Approach of LightGBM and Stratified KFold Cross-Validation

Abstract

This research article aims to develop a robust and interpretable model for energy efficiency and classification that overcomes the limitations of existing techniques. The study’s objectives are to address the challenges faced by the established methods such as linear regression, random forest, support vector machines, and others. These limitations include issues related to predictive accuracy, model interpretability, and computational efficiency. To bridge these gaps, we introduce a novel model, stratified KFold LightGBM ensemble (SKL-EEFE). SKL-EEFE leverages the strengths of stratified KFold cross-validation, LightGBM gradient boosting, domain-specific feature engineering, and ensemble learning to provide a comprehensive solution to classification tasks. Our key findings reveal that SKL-EEFE outperforms existing methods while maintaining model interpretability. The proposed model offers both accuracy and transparency, making it a valuable addition to the field of classification modeling. This research contributes to advancing the state of knowledge by offering an innovative approach to overcome the limitations of existing models and providing a practical solution for real-world classification problems.

Keywords:

• classification modeling
• machine learning
• ensemble learning
• LightGBM
• stratified KFold cross-validation
• model interpretability
• feature engineering
• computational efficiency
• predictive accuracy
• classification tasks

Acknowledgments

There is no acknowledgment involved in this work.

Authorship Contributions

All authors contributed equally to this work.

Disclosure Statement

No potential conflict of interest was reported by the author(s).

Ethics Approval and Consent to Participate

No participation of humans takes place in this implementation process.

Human and Animal Rights

No violation of human and animal rights is involved.

Conflicts of Interest

No potential conflict of interest was reported by the author(s).

Data Availability Statement

Data sharing is not applicable to this article as no datasets were generated or analyzed during the current study.

Additional information

Funding

The authors received no specific funding for this study.

Notes on contributors

Sushma Kakkar

Sushma Kakkar received the bachelor’s degree in Engineering in Electrical Engineering from NIT Kurukshetra, India and Master Degree in Power Electronics, Electric Machines and Drives from IIT Delhi, India. She obtained her Ph.D from Indian Institute of Technology (ISM), Dhanbad, Jharkhand, India. She is currently working as Associate Professor in Department of Electrical Electronics and Communication Engineering Department, Sharda University, Greater Noida, India. Her areas of research interest include power electronics and Drives, power quality, and distributed generation.

A. Jaya Lakshmi

A. Jaya Lakshmi stands as a dedicated and accomplished professional in the field of wireless communications, holding a prestigious Ph.D. degree in the subject from JNTUA Ananthapuramu, located in Andhra Pradesh, India. Currently serving as an Assistant Professor in the ECE (Electronics and Communication Engineering) department at Vardhaman College of Engineering, situated in Hyderabad, Telangana, India, with an impressive tenure of 15 years in the field of teaching, Dr. Jaya Lakshmi has made significant contributions to the education and development of aspiring engineers. Dr. Jaya Lakshmi’s research endeavours have resulted in the publication of 28 papers in various international journals and conferences. Her scholarly work covers a diverse range of topics within the broad spectrum of technology, including wireless communications, embedded systems, computer vision, image processing, signal processing, machine learning and Deep learning. This multifaceted research portfolio reflects her keen interest in staying at the forefront of technological advancements and contributing valuable insights to the academic and professional communities. Her commitment to excellence in both teaching and research underscores her significant impact on the academic community and the broader field of technology.

Anand Deva Durai C

Anand Deva Durai C received his Masters of Science in Software Engineering from Madurai Kamraj University in 2004 and Masters in Computer Science and Engineering from Anna University, Chennai, in 2007. He has received his PhD degree in Computer Science and Engineering from Manomaniam Sundaranar University, Tirunelveli, by 2013. With 15+ years of experience in teaching and research, currently he is working as an Associate Professor in the College of Computer Science, King Khalid University, Saudi Arabia. His primary research interests lie in Machine Learning, Artificial Intelligence and Evolutionary Computing, Pattern recognition, etc. He is a life time member of the Computer Society of India. Email: [email protected].

Wakeel Ahmad

Wakeel Ahmad is currently working as an Assistant Professor in the Department of Electrical Engineering Technology, College of Applied Industrial Technology (CAIT), Baish under Jazan University, Jazan, Kingdom of Saudi Arabia. He obtained his Ph.D (Electronics) and M. Tech (Electronics Design and Technology) from Magadh University, Bodg-Gaya and Tezpur University (Central University), Assam, India in 2014 and 2002, respectively. He worked as a research scholar in the research and development group at CEERI, Pilani, Rajasthan, India.

Mohamed Uvaze Ahamed Ayoobkhan

Mohamed Uvaze Ahamed Ayoobkhan having obtained both Bachelor’s and Master’s degrees from Anna University, Chennai, India, furthered his academic journey by earning a PhD in Information Technology, honored with the Best PhD Thesis Award in 2018 from Multimedia University, Malaysia. With teaching roles at Sri Ramakrishna Engineering College and Jain University in India, he expanded his academic horizons to encompass positions in Iraq and Uzbekistan. Presently, he serves as an Assistant Professor at New Uzbekistan University, Tashkent. Dr. Mohamed’s scholarly endeavors extend beyond teaching, boasting 6 international Intellectual Property Rights and a robust publication record exceeding 40 research papers in esteemed international journals and conferences. His research focuses primarily on Computer Vision and Machine Learning, particularly in Medical Imaging, Optimization, and Deep/Shallow Learning. Dr. Mohamed actively contributes to the academic community as a guest editor, advisory board member, and reviewer for prestigious international journals and conferences, reflecting his unwavering commitment to advancing knowledge in his field.

P. Veeramanikandan

P. Veeramanikandan (1982) was born in Ramanathapuram, Tamilnadu, India, in 1982, Tamilnadu, India. He received B.E degree in Electrical and Electronics Engineering and M.E degree in Power Electronics and Drives both from Anna University, Chennai in 2010 and 2012, respectively and the Ph.D. degree in electrical engineering from Anna University, Chennai, Tamilnadu, in 2021. He is working as an Associate Professor in the Department of Electrical & Electronics Engineering at Jaya Engineering College, Chennai, Tamilnadu, India. His research interests are in the area of Power Electronics, Solar MPPT, Multilevel Inverter and Soft computing techniques.

P. Nagasekhar Reddy

P. Nagasekhar Reddy Associate Professor received his M.Tech degree from Jawaharlal Nehru technological University, Hyderabad, India in 2005 and completed his Ph.D from Jawaharlal Nehru technological University, Hyderabad in 2014. He is presently working as Associate Professor in Mahatma Gandhi Institute of Technology, Hyderabad, India. He presented more than 60 research papers in various national and international Journals and Conferences. His research areas include Power Electronics, PWM techniques, DC to AC converters and control of electrical drives. He authored 5 Text Books published by national and international publishers and has 4 patent publications into his credit.

Vijay Kumar Dwivedi

Vijay Kumar Dwivedi is presently an Assistant Professor of Mathematics at Vishwavidyalaya Engineering College Ambikapur (C.G.), worked as Head of Applied Science Department. He is involved in teaching UG, PG classes and in Ph.D. course work for over 23 years. He has contributed the subject by researching Fuzzy and Set-Theoretic Approach to Game Theory. He has many patents; is the author of national and international research papers and has organized different national conferences. He is author of the books “Engineering Mathematics”, “Graph Theory”, “Discrete Mathematics and Graph Theory” & “Applied Numerical Methods”. He is editor of E-Book and has contributed in the translation of AICTE question bank of the subjects ‘Mathematics’ and ‘Mental Ability’ for implementation of ASLAP in Hindi language. He is also a life member of Indian Mathematical Society.

A. Rajaram

A. Rajaram received the B.E. degree in Electronics and Communication Engineering from the Government, College of Technology, Coimbatore, Anna University, Chennai, India, in 2006, the M.E. degree in Applied Electronics from the Government College of Technology, Anna University, Chennai, India, in 2008 and he received the Full Time Ph.D. degree in Electronics and Communication Engineering from the Anna University of Technology, Coimbatore, India in March 2011. He is currently working as a professor in Department of Electronics and Communication Engineering, E.G.S Pillay Engineering College, Nagapattinam. His research interests include Mobile Ad Hoc networks, wireless communication networks (WiFi, WiMax HighSlot GSM), novel VLSI NoC Design approaches to address issues such as low-power, cross-talk, hardware acceleration, Design issues includes OFDM MIMO and noise Suppression in MAI Systems, ASIC design, Control systems, Fuzzy logic and Networks, AI, Sensor Networks.