Support of

`randomForest`

and`ranger`

models which have been created using`parsnip`

Fix class checking for when formula notation is used in randomForest

Significant reduction in compute time for calculating false positive rates by sampling only unique selection frequencies

Addition of

`tidy`

tools (dplyr, tibble, magrittr)

`internals`

now implemented in C++*via*`Rcpp`

thanks to Dr Jasen Finch (@jasenfinch)

Implemented Strategy-1 from

*Konukoglu,E. and Ganz,M.,2014*.**Approximate false positive rate control in selection frequency for random forest**Support for

`randomForest`

and`ranger`

forest objectsCalculate selection frequency threshold for a given false positive rate (alpha)

False positive rate feature selection

Wrapper for selection frequencies extract from objects