Determine and Evaluate Optimal Cutpoints in Binary
Classification Tasks
person("Christian", "Thiele", , "c.thiele@hs-osnabrueck.de", c("aut", "cre"))
Estimate cutpoints that optimize a specified metric in binary classification tasks
and validate performance using bootstrapping. Some methods for more robust cutpoint
estimation and various plotting functions are included.

person("Christian", "Thiele", , "c.thiele@gmx-topmail.de", c("aut", "cre"))

person(given = "Christian",
family = "Thiele",
role = c("cre", "aut"),
email = "c.thiele@gmx-topmail.de",
comment = c(ORCID = "0000-0002-1156-5117"))
Estimate cutpoints that optimize a specified metric in binary classification tasks
and validate performance using bootstrapping. Some methods for more robust cutpoint
estimation are supported, e.g. a parametric method assuming normal distributions,
bootstrapped cutpoints, and smoothing of the metric values per cutpoint using
Generalized Additive Models. Various plotting functions are included. For an overview
of the package see 'Thiele and Hirschfeld (2020)' <arXiv:2002.09209>.
Christian Thiele [cre, aut] (<https://orcid.org/0000-0002-1156-5117>)

Estimate cutpoints that optimize a specified metric in binary classification tasks
and validate performance using bootstrapping. Some methods for more robust cutpoint
estimation are supported, e.g. a parametric method assuming normal distributions,
bootstrapped cutpoints, and smoothing of the metric values per cutpoint using
Generalized Additive Models. Various plotting functions are included. For an overview
of the package see Thiele and Hirschfeld (2020) <arXiv:2002.09209>.

Estimate cutpoints that optimize a specified metric in binary classification tasks
and validate performance using bootstrapping. Some methods for more robust cutpoint
estimation are supported, e.g. a parametric method assuming normal distributions,
bootstrapped cutpoints, and smoothing of the metric values per cutpoint using
Generalized Additive Models. Various plotting functions are included. For an overview
of the package see Thiele and Hirschfeld (2021) <doi:10.18637/jss.v098.i11>.