A Machine Learning Model to Prune Insignificant Attributes

• Published in: 2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO) pp. 1 - 6
• Main Authors: Agarwal, Nidhi, Bajaj, Neetika Arora, Ratan, Manjeet Kaur, Deep, Prakhar
• Format: Conference Proceeding
• Language: English
• Published: IEEE 03.09.2021
• Subjects: accuracy; hypothesis testing; Linear regression; Machine learning; Optimization; p-value; prediction; Predictive models; Reliability; significant feature

In this research work, a machine learning model is proposed with only those features which are significantly contributing in prediction using multiple linear regression. The other insignificant features are pruned or eliminated using the concept of p-value. The research work will use p-value solely...