Version 0.2.2

• Routine house-keeping
• Update citation url

Version 0.2.1

• Bug fix for class checking when formula notation has been used
• Support for randomForest and ranger models which have been created using parsnip

v0.2.0

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

• Addition of tidy tools (dplyr, tibble, magrittr)

v0.1.1

• Core algorithm now implemented in C++
• Ready for CRAN submission

v.0.1.0

v0.1.0

• 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 objects

• Calculate selection frequency threshold for a given false positive rate (alpha)

• False positive rate feature selection

• Wrapper for selection frequencies extract from objects