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

    Metadata Updated: January 21, 2026

    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.

    Access & Use Information

    Public: This dataset is intended for public access and use. License: No license information was provided. If this work was prepared by an officer or employee of the United States government as part of that person's official duties it is considered a U.S. Government Work.

    Downloads & Resources

    Dates

    Metadata Created Date January 12, 2026
    Metadata Updated Date January 21, 2026

    Metadata Source

    Harvested from DOI USGS DCAT-US

    Other Data Resources

    Additional Metadata

    Resource Type Dataset
    Metadata Created Date January 12, 2026
    Metadata Updated Date January 21, 2026
    Publisher U.S. Geological Survey
    Maintainer
    Identifier http://datainventory.doi.gov/id/dataset/USGS_647a3349d34eac007b521f2d
    Data Last Modified 2023-10-04T00:00:00Z
    Category geospatial
    Public Access Level public
    Bureau Code 010:12
    Metadata Context https://project-open-data.cio.gov/v1.1/schema/catalog.jsonld
    Metadata Catalog ID https://ddi.doi.gov/usgs-data.json
    Schema Version https://project-open-data.cio.gov/v1.1/schema
    Catalog Describedby https://project-open-data.cio.gov/v1.1/schema/catalog.json
    Datagov Dedupe Retained 20260121130127
    Harvest Object Id 3ed1067a-7633-4155-981b-834ca874560a
    Harvest Source Id 2b80d118-ab3a-48ba-bd93-996bbacefac2
    Harvest Source Title DOI USGS DCAT-US
    Metadata Type geospatial
    Old Spatial {"type": "Polygon", "coordinates": -127.7930, 24.0465, -127.7930, 49.8380, -64.6875, 49.8380, -64.6875, 24.0465, -127.7930, 24.0465}
    Source Datajson Identifier True
    Source Hash d11938b2b321349a64ee3e31159184ed33e2db34d7f975c0925a942c9b4cb4eb
    Source Schema Version 1.1
    Spatial {"type": "Polygon", "coordinates": -127.7930, 24.0465, -127.7930, 49.8380, -64.6875, 49.8380, -64.6875, 24.0465, -127.7930, 24.0465}

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