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 in2021 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
LanguageEnglish
Published IEEE 03.09.2021
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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.
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
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  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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