Feature Selection And Model Performance Analysis

Authors: Ms Dimpy, Vanshika Dubey, Sakshi Kumari, Aarzia Juned

Abstract: Feature selection is an important step in machine learning that helps improve model performance by removing irrelevant and redundant data. This study compares different feature selection techniques and analyzes their impact on various models. Results show that proper feature selection reduces complexity, improves accuracy, and prevents overfitting, leading to better overall model performance.

DOI: https://doi.org/10.5281/zenodo.20198033