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  "Package": "randomForestVIP",
  "Title": "Tune Random Forests Based on Variable Importance and Plot\nResults",
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  "Authors@R": "c(person(\"Kelvyn\", \"Bladen\", role = c(\"aut\", \"cre\"), \nemail = \"kelvyn.bladen@usu.edu\"),\nperson(given=c(\"D.\", \"Richard\"), \"Cutler\", role = \"aut\"))",
  "Description": "Functions for assessing variable relations and\nassociations prior to modeling with a Random Forest algorithm\n(although these are relevant for any predictive model). Metrics\nsuch as partial correlations and variance inflation factors are\ntabulated as well as plotted for the user. A function is\navailable for tuning the main Random Forest hyper-parameter\nbased on model performance and variable importance metrics.\nThis grid-search technique provides tables and plots showing\nthe effect of the main hyper-parameter on each of the\nassessment metrics. It also returns each of the evaluated\nmodels to the user. The package also provides superior variable\nimportance plots for individual models. All of the plots are\ndeveloped so that the user has the ability to edit and improve\nfurther upon the plots. Derivations and methodology are\ndescribed in Bladen (2022)\n<https://digitalcommons.usu.edu/etd/8587/>.",
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  "Date/Publication": "2023-12-01 20:04:42 UTC",
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