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The caret package (short for Classification And REgression Training) is a set of functions that attempt to streamline the process for creating predictive models. The package contains tools for:

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  • data splitting
  • pre-processing
  • feature selection
  • model tuning using resampling
  • variable importance estimation

as 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).

The current release version can be found on CRAN and the project is hosted on github.

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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.

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In the vast majority of cases, the solution is to properly reinstall ext-ms-win-ntuser-caret-l1-1-0.dll on your PC, to the Windows system folder. Alternatively, some programs, notably PC games, require that the DLL file is placed in the game/application installation folder.

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