{
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  "Title": "Spatiotemporal Resampling Methods for 'mlr3'",
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  "Authors@R": "c(\nperson(\"Patrick\", \"Schratz\", , \"patrick.schratz@gmail.com\", role = c(\"aut\", \"cre\"),\ncomment = c(ORCID = \"0000-0003-0748-6624\")),\nperson(\"Marc\", \"Becker\", , \"marcbecker@posteo.de\", role = \"aut\",\ncomment = c(ORCID = \"0000-0002-8115-0400\")),\nperson(\"Jannes\", \"Muenchow\", , \"jannes.muenchow@uni-jena.de\", role = \"ctb\",\ncomment = c(ORCID = \"0000-0001-7834-4717\")),\nperson(\"Michel\", \"Lang\", , \"michellang@gmail.com\", role = \"ctb\",\ncomment = c(ORCID = \"0000-0001-9754-0393\"))\n)",
  "Description": "Extends the mlr3 machine learning framework with\nspatio-temporal resampling methods to account for the presence\nof spatiotemporal autocorrelation (STAC) in predictor\nvariables. STAC may cause highly biased performance estimates\nin cross-validation if ignored. A JSS article is available at\n<doi:10.18637/jss.v111.i07>.",
  "License": "LGPL-3",
  "URL": "https://mlr3spatiotempcv.mlr-org.com/,\nhttps://github.com/mlr-org/mlr3spatiotempcv,\nhttps://mlr3book.mlr-org.com",
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  "Repository": "https://mlr-org.r-universe.dev",
  "Date/Publication": "2025-09-12 09:41:42 UTC",
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  "Author": "Patrick Schratz [aut, cre] (ORCID:\n<https://orcid.org/0000-0003-0748-6624>),\nMarc Becker [aut] (ORCID: <https://orcid.org/0000-0002-8115-0400>),\nJannes Muenchow [ctb] (ORCID: <https://orcid.org/0000-0001-7834-4717>),\nMichel Lang [ctb] (ORCID: <https://orcid.org/0000-0001-9754-0393>)",
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      "title": "mlr3spatiotempcv: Spatiotemporal Resampling Methods for 'mlr3'",
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        "mlr3spatiotempcv"
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        "as_task_regr_st.DataBackend",
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        "plot.ResamplingCV",
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        "autoplot.ResamplingSpCVBlock",
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      "title": "Visualization Functions for SpCV Buffer Methods.",
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        "autoplot.ResamplingSptCVCstf",
        "plot.ResamplingRepeatedSptCVCstf",
        "plot.ResamplingSptCVCstf"
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      "page": "mlr_resamplings_repeated_spcv_block",
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