An Efficient Elastic Net with Regression Coefficients Method for Variable Selection of Spectrum Data.
Using the spectrum data for quality prediction always suffers from noise and colinearity, so variable selection method plays an important role to deal with spectrum data. An efficient elastic net with regression coefficients method (Enet-BETA) is proposed to select the significant variables of the s...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2017-01-01
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| Series: | PLoS ONE |
| Online Access: | http://europepmc.org/articles/PMC5289531?pdf=render |
| _version_ | 1828437169409097728 |
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| author | Wenya Liu Qi Li |
| author_facet | Wenya Liu Qi Li |
| author_sort | Wenya Liu |
| collection | DOAJ |
| description | Using the spectrum data for quality prediction always suffers from noise and colinearity, so variable selection method plays an important role to deal with spectrum data. An efficient elastic net with regression coefficients method (Enet-BETA) is proposed to select the significant variables of the spectrum data in this paper. The proposed Enet-BETA method can not only select important variables to make the quality easy to interpret, but also can improve the stability and feasibility of the built model. Enet-BETA method is not prone to overfitting because of the reduction of redundant variables realized by elastic net method. Hypothesis testing is used to further simplify the model and provide a better insight into the nature of process. The experimental results prove that the proposed Enet-BETA method outperforms the other methods in terms of prediction performance and model interpretation. |
| first_indexed | 2024-12-10T19:40:19Z |
| format | Article |
| id | doaj.art-27cbcc171295458380c888daecdedb33 |
| institution | Directory Open Access Journal |
| issn | 1932-6203 |
| language | English |
| last_indexed | 2024-12-10T19:40:19Z |
| publishDate | 2017-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj.art-27cbcc171295458380c888daecdedb332022-12-22T01:36:01ZengPublic Library of Science (PLoS)PLoS ONE1932-62032017-01-01122e017112210.1371/journal.pone.0171122An Efficient Elastic Net with Regression Coefficients Method for Variable Selection of Spectrum Data.Wenya LiuQi LiUsing the spectrum data for quality prediction always suffers from noise and colinearity, so variable selection method plays an important role to deal with spectrum data. An efficient elastic net with regression coefficients method (Enet-BETA) is proposed to select the significant variables of the spectrum data in this paper. The proposed Enet-BETA method can not only select important variables to make the quality easy to interpret, but also can improve the stability and feasibility of the built model. Enet-BETA method is not prone to overfitting because of the reduction of redundant variables realized by elastic net method. Hypothesis testing is used to further simplify the model and provide a better insight into the nature of process. The experimental results prove that the proposed Enet-BETA method outperforms the other methods in terms of prediction performance and model interpretation.http://europepmc.org/articles/PMC5289531?pdf=render |
| spellingShingle | Wenya Liu Qi Li An Efficient Elastic Net with Regression Coefficients Method for Variable Selection of Spectrum Data. PLoS ONE |
| title | An Efficient Elastic Net with Regression Coefficients Method for Variable Selection of Spectrum Data. |
| title_full | An Efficient Elastic Net with Regression Coefficients Method for Variable Selection of Spectrum Data. |
| title_fullStr | An Efficient Elastic Net with Regression Coefficients Method for Variable Selection of Spectrum Data. |
| title_full_unstemmed | An Efficient Elastic Net with Regression Coefficients Method for Variable Selection of Spectrum Data. |
| title_short | An Efficient Elastic Net with Regression Coefficients Method for Variable Selection of Spectrum Data. |
| title_sort | efficient elastic net with regression coefficients method for variable selection of spectrum data |
| url | http://europepmc.org/articles/PMC5289531?pdf=render |
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