Impact of Box-Cox Transformation on Machine-Learning Algorithms
This paper studied the effects of applying the Box-Cox transformation for classification tasks. Different optimization strategies were evaluated, and the results were promising on four synthetic datasets and two real-world datasets. A consistent improvement in accuracy was demonstrated using a grid...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-04-01
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| Series: | Frontiers in Artificial Intelligence |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/frai.2022.877569/full |
| _version_ | 1818202074027917312 |
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| author | Luca Blum Mohamed Elgendi Carlo Menon |
| author_facet | Luca Blum Mohamed Elgendi Carlo Menon |
| author_sort | Luca Blum |
| collection | DOAJ |
| description | This paper studied the effects of applying the Box-Cox transformation for classification tasks. Different optimization strategies were evaluated, and the results were promising on four synthetic datasets and two real-world datasets. A consistent improvement in accuracy was demonstrated using a grid exploration with cross-validation. In conclusion, applying the Box-Cox transformation could drastically improve the performance by up to a 12% accuracy increase. Moreover, the Box-Cox parameter choice was dependent on the data and the used classifier. |
| first_indexed | 2024-12-12T03:03:40Z |
| format | Article |
| id | doaj.art-48231d02c74445b0af657d3a8f415dbd |
| institution | Directory Open Access Journal |
| issn | 2624-8212 |
| language | English |
| last_indexed | 2024-12-12T03:03:40Z |
| publishDate | 2022-04-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Artificial Intelligence |
| spelling | doaj.art-48231d02c74445b0af657d3a8f415dbd2022-12-22T00:40:34ZengFrontiers Media S.A.Frontiers in Artificial Intelligence2624-82122022-04-01510.3389/frai.2022.877569877569Impact of Box-Cox Transformation on Machine-Learning AlgorithmsLuca BlumMohamed ElgendiCarlo MenonThis paper studied the effects of applying the Box-Cox transformation for classification tasks. Different optimization strategies were evaluated, and the results were promising on four synthetic datasets and two real-world datasets. A consistent improvement in accuracy was demonstrated using a grid exploration with cross-validation. In conclusion, applying the Box-Cox transformation could drastically improve the performance by up to a 12% accuracy increase. Moreover, the Box-Cox parameter choice was dependent on the data and the used classifier.https://www.frontiersin.org/articles/10.3389/frai.2022.877569/fullBox-Cox transformationpower transformationNon-linear mappingsfeature transformationaccuracy improvementclassifier optimization |
| spellingShingle | Luca Blum Mohamed Elgendi Carlo Menon Impact of Box-Cox Transformation on Machine-Learning Algorithms Frontiers in Artificial Intelligence Box-Cox transformation power transformation Non-linear mappings feature transformation accuracy improvement classifier optimization |
| title | Impact of Box-Cox Transformation on Machine-Learning Algorithms |
| title_full | Impact of Box-Cox Transformation on Machine-Learning Algorithms |
| title_fullStr | Impact of Box-Cox Transformation on Machine-Learning Algorithms |
| title_full_unstemmed | Impact of Box-Cox Transformation on Machine-Learning Algorithms |
| title_short | Impact of Box-Cox Transformation on Machine-Learning Algorithms |
| title_sort | impact of box cox transformation on machine learning algorithms |
| topic | Box-Cox transformation power transformation Non-linear mappings feature transformation accuracy improvement classifier optimization |
| url | https://www.frontiersin.org/articles/10.3389/frai.2022.877569/full |
| work_keys_str_mv | AT lucablum impactofboxcoxtransformationonmachinelearningalgorithms AT mohamedelgendi impactofboxcoxtransformationonmachinelearningalgorithms AT carlomenon impactofboxcoxtransformationonmachinelearningalgorithms |