Basic Statistical Estimation Outperforms Machine Learning in Monthly Prediction of Seasonal Climatic Parameters Article Swipe
Eslam A. Hussein
,
Mehrdad Ghaziasgar
,
Christopher Thron
,
M. Vaccari
,
Antoine Bagula
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.3390/atmos12050539
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.3390/atmos12050539
Machine learning (ML) has been utilized to predict climatic parameters, and many successes have been reported in the literature. In this paper, we scrutinize the effectiveness of five widely used ML algorithms in the monthly prediction of seasonal climatic parameters using monthly image data. Specifically, we quantify the predictive performance of these algorithms applied to five climatic parameters using various combinations of features. We compare the predictive accuracy of the resulting trained ML models to that of basic statistical estimators that are computed directly from the training data. Our results show that ML never significantly outperforms the statistical baseline, and underperforms for most feature sets. Unlike previous similar studies, we provide error bars for the relative performance of different predictors based on jackknife estimates applied to differences in predictive error magnitudes. We also show that the practice of shuffling data sequences which was employed in some previous references leads to data leakage, resulting in over-estimated performance. Ultimately, the paper demonstrates the importance of using well-grounded statistical techniques when producing and analyzing the results of ML predictive models.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/atmos12050539
- https://www.mdpi.com/2073-4433/12/5/539/pdf?version=1619146694
- OA Status
- gold
- Cited By
- 9
- References
- 91
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3156671431
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Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3156671431Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.3390/atmos12050539Digital Object Identifier
- Title
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Basic Statistical Estimation Outperforms Machine Learning in Monthly Prediction of Seasonal Climatic ParametersWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2021Year of publication
- Publication date
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2021-04-23Full publication date if available
- Authors
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Eslam A. Hussein, Mehrdad Ghaziasgar, Christopher Thron, M. Vaccari, Antoine BagulaList of authors in order
- Landing page
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https://doi.org/10.3390/atmos12050539Publisher landing page
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https://www.mdpi.com/2073-4433/12/5/539/pdf?version=1619146694Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
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goldOpen access status per OpenAlex
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https://www.mdpi.com/2073-4433/12/5/539/pdf?version=1619146694Direct OA link when available
- Concepts
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Jackknife resampling, Estimator, Computer science, Machine learning, Predictive modelling, Feature (linguistics), Mean squared prediction error, Artificial intelligence, Data mining, Statistics, Mathematics, Linguistics, PhilosophyTop concepts (fields/topics) attached by OpenAlex
- Cited by
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9Total citation count in OpenAlex
- Citations by year (recent)
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2025: 1, 2024: 1, 2023: 3, 2022: 3, 2021: 1Per-year citation counts (last 5 years)
- References (count)
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91Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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