A Machine Learning Model to Prune Insignificant Attributes
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...
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Published in | 2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO) pp. 1 - 6 |
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Main Authors | , , , |
Format | Conference Proceeding |
Language | English |
Published |
IEEE
03.09.2021
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Subjects | |
Online Access | Get full text |
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Abstract | 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 to determine which features are significant to the dataset and which are not so important. The results obtained are quite promising in terms of prediction power of the novel model as compared to the work done in literature till now. |
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AbstractList | 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 to determine which features are significant to the dataset and which are not so important. The results obtained are quite promising in terms of prediction power of the novel model as compared to the work done in literature till now. |
Author | Bajaj, Neetika Arora Deep, Prakhar Agarwal, Nidhi Ratan, Manjeet Kaur |
Author_xml | – sequence: 1 givenname: Nidhi surname: Agarwal fullname: Agarwal, Nidhi email: nidhiagarwal82@gmail.com organization: IGDTUW,CSE Department,Delhi,India – sequence: 2 givenname: Neetika Arora surname: Bajaj fullname: Bajaj, Neetika Arora email: manjeetratan@gmail.com organization: SUNDERDEEP COLLEGE OF MGMT. &TECHNOLOGY,Ghaziabad,India – sequence: 3 givenname: Manjeet Kaur surname: Ratan fullname: Ratan, Manjeet Kaur email: neetikaarorabajaj@gmail.com organization: IINCORE SOFTWARE SYSTEM,Noida,India – sequence: 4 givenname: Prakhar surname: Deep fullname: Deep, Prakhar email: prakhar.deep@techmahindra.com organization: Tech Mahindra,Noida,India |
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Snippet | In this research work, a machine learning model is proposed with only those features which are significantly contributing in prediction using multiple linear... |
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SubjectTerms | accuracy hypothesis testing Linear regression Machine learning Optimization p-value prediction Predictive models Reliability significant feature |
Title | A Machine Learning Model to Prune Insignificant Attributes |
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