codemeta.json

{
  "@context": "https://doi.org/10.5063/schema/codemeta-2.0",
  "@type": "SoftwareSourceCode",
  "author": [
    {
      "@id": "https://orcid.org/0000-0003-3140-537X",
      "@type": "Person",
      "familyName": "Topçuoğlu",
      "givenName": "Begüm"
    },
    {
      "@id": "https://orcid.org/0000-0003-4674-2176",
      "@type": "Person",
      "familyName": "Lapp",
      "givenName": "Zena"
    },
    {
      "@id": "https://orcid.org/0000-0003-3283-829X",
      "@type": "Person",
      "familyName": "Sovacool",
      "givenName": "Kelly"
    },
    {
      "@id": "https://orcid.org/0000-0001-8409-278X",
      "@type": "Person",
      "familyName": "Snitkin",
      "givenName": "Evan"
    },
    {
      "@id": "https://orcid.org/0000-0002-1057-7722",
      "@type": "Person",
      "familyName": "Wiens",
      "givenName": "Jenna"
    },
    {
      "@id": "https://orcid.org/0000-0002-6935-4275",
      "@type": "Person",
      "familyName": "Schloss",
      "givenName": "Patrick"
    }
  ],
  "codeRepository": "https://github.com/SchlossLab/mikropml",
  "description": "An interface to build machine learning models for classification and regression problems. 'mikropml' implements the ML pipeline described by Topçuoğlu et al. (2020) <https://doi.org/10.1128/mBio.00434-20> with reasonable default options for data preprocessing, hyperparameter tuning, cross-validation, testing, model evaluation, and interpretation steps. See the website <https://www.schlosslab.org/mikropml/> for more information, documentation, and examples.",
  "identifier": "https://doi.org/10.21105/joss.03073",
  "keywords": [
    "machine-learning",
    "r-package",
    "rstats"
  ],
  "license": "https://spdx.org/licenses/MIT",
  "name": "mikropml: User-Friendly R Package for Supervised Machine Learning Pipelines",
  "url": "https://www.schlosslab.org/mikropml/"
}