Prediction Intervals with Random Forests and Boosted Forests

Implements various prediction interval methods with random forests and boosted forests. The package has two main functions: pibf() produces prediction intervals with boosted forests (PIBF) as described in Alakus et al. (2021) and rfpi() builds 15 distinct variations of prediction intervals with random forests (RFPI) proposed by Roy and Larocque (2020) .


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install.packages("RFpredInterval")

1.0.4 by Cansu Alakus, 11 days ago


https://github.com/calakus/RFpredInterval


Report a bug at https://github.com/calakus/RFpredInterval/issues


Browse source code at https://github.com/cran/RFpredInterval


Authors: Cansu Alakus [aut, cre] , Denis Larocque [aut] , Aurelie Labbe [aut] , Hemant Ishwaran [ctb] (Author of included randomForestSRC codes) , Udaya B. Kogalur [ctb] (Author of included randomForestSRC codes)


Documentation:   PDF Manual  


GPL (>= 3) license


Imports ranger, data.table, hdrcde, parallel, data.tree, DiagrammeR

Suggests knitr, rmarkdown, testthat


See at CRAN