The caret package (short for _C_lassification _A_nd _RE_gression _T_raining) is a set of functions… The caret package (short for _C_lassification _A_nd _RE_gression _T_raining) is a set of functions that attempt to streamline the process for creating predictive models. The package contains tools for: data splitting pre-processing feature selection model tuning using resampling variable importance estimationas well as other functionality.There are many different modeling functions in R. Some have different syntax for model training and/or prediction. The package started off as a way to provide a uniform interface the functions themselves, as well as a way to standardize common tasks (such parameter tuning and variable importance). More Info »The current release version can be found on CRAN and the project is hosted on github.Some resources: The book Applied Predictive Modeling features caret and over 40 other R packages. It is on sale at Amazon or the the publisher’s website. There is a companion website too. There is also a paper on caret in the Journal of Statistical Software. The example data can be obtained here(the predictors) and here (the outcomes). There is a webinar for the package on Youtube that was organized and recorded by Ray DiGiacomo Jr for the Orange County R User Group. At useR! 2014, I was interviewed and discussed the package and the book. DataCamp has a beginner’s tutorial on machine learning in R using caret.You can always email me with questions,comments or suggestions.These HTML pages were created using bookdown.
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