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Data to support Leveraging machine learning to automate regression model evaluations for large multi-site water-quality trend studies

This data release contains one dataset and one model archive in support of the journal article "Leveraging machine learning to automate regression model evaluations for large multi-site water-quality trend studies" by Jennifer C. Murphy and Jeffrey G. Chanat. The model archive contains scripts (run in R) to reproduce the four machine learning models (logistic regression, linear and quadratic discriminant analysis, and k-nearest neighbors) trained and tested as part of the journal article. The dataset contains the estimated probabilities for each of these models when applied to a training and test dataset.

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Author(s) Jennifer C Murphy orcid, Jeffrey G Chanat
Publication Date 2023-10-04
Beginning Date of Data 2017
Ending Date of Data 2019
Data Contact
DOI https://doi.org/10.5066/P9GNEN8S
Citation Murphy, J.C., and Chanat, J.G., 2023, Data to support Leveraging machine learning to automate regression model evaluations for large multi-site water-quality trend studies: U.S. Geological Survey data release, https://doi.org/10.5066/P9GNEN8S.
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Metadata Date 2023-10-04
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Citations of these data

Loading https://doi.org/10.1016/j.envsoft.2023.105864

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License http://www.usa.gov/publicdomain/label/1.0/
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Harvest Source: ScienceBase
Harvest Date: 2024-02-24T09:44:24.901Z