Speaker:

Dr. Satya Verma of ITER, Bhubaneswar

Topic:

Feature Selection in Machine Learning

ABSTRACT:

Feature selection is a critical preprocessing step in machine learning that aims to identify the most relevant attributes from high‑dimensional datasets. By eliminating redundant and irrelevant features, it reduces computational complexity, mitigates overfitting, and enhances model generalization. Effective feature selection improves learning accuracy while maintaining interpretability, making models more transparent and efficient. Techniques are broadly categorized into filter methods, which rely on statistical measures; wrapper methods, which evaluate subsets using predictive models; and embedded methods, which integrate selection during model training. Recent advances also explore hybrid approaches and evolutionary algorithms to balance accuracy and efficiency. Applications span diverse domains such as bioinformatics, text mining, and healthcare analytics, where large feature spaces are common. Overall, feature selection not only accelerates training but also strengthens decision‑making, ensuring robust and scalable machine learning solutions for complex real‑world problems.

Biography:

Dr. Satya Verma is currently working as Assistant professor in the Department of CSE, Institute of Technical Education and Research, Siksha ‘O’ Anusandhan, Bhubaneswar, India. She has received Ph.D. degree from National Institute of Technology, Raipur, India in 2024, M. Tech. (Honors) degree from National Institute of Technology, Raipur, India in 2011, and B.E. degree from Pt. Ravishankar Shukla University, Raipur, India in 2003. She has total 18 years of academic experience in different engineering colleges. She has good number of research article publications in various SCI/Scopus journals and international conferences as well. Apart from publications, she has one utility patent and two design patents. Her research interest includes Feature Engineering, Feature Selection Techniques, Meta-heuristic Optimization, Machine Learning and Deep Learning, Financial Time Series Analysis, Natural Language Processing, and Image Processing.

Address:CSE, Institute of Technical Education and Research, Siksha ‘O’ Anusandhan, , Bhubaneswar, Orissa, India