Title: Data preprocessing, discretization for classification.
Description: This package is a collection of supervised discretization

Maintainer: Kim, H. J. <polaris7867@gmail.com>

Title: Model Wrappers for Discriminant Analysis
Description: Bindings for additional classification models for use with the
'parsnip' package. Models include flavors of discriminant analysis, such as
as well as naive Bayes classifiers (Hand and Yu (2007)
Imports: purrr, rlang, tibble, withr, dials
Suggests: testthat, MASS, mda, klaR, earth, mlbench, covr, ggplot2,

Description: Bindings for additional classification models for use with
the 'parsnip' package. Models include flavors of discriminant
well as naive Bayes classifiers (Hand and Yu (2007)
Imports: dials, purrr, rlang, tibble, utils, withr
Suggests: covr, dplyr, earth, ggplot2, klaR, MASS, mda, mlbench,
modeldata, naivebayes, sda, sparsediscrim (>= 0.3.0), spelling,

Imports: dials, purrr, rlang, tibble, withr

person("Emil", "Hvitfeldt", , "emilhhvitfeldt@gmail.com", role = c("aut", "cre"),
person("Max", "Kuhn", , "max@rstudio.com", role = c("aut"),
Suggests: covr, dplyr, earth, ggplot2, klaR, knitr, MASS, mda, mlbench,
modeldata, naivebayes, rmarkdown, sda, sparsediscrim (>=
0.3.0), spelling, testthat (>= 3.0.0), xml2
Packaged: 2022-06-23 00:00:01 UTC; emilhvitfeldt
Author: Emil Hvitfeldt [aut, cre] (<https://orcid.org/0000-0002-0679-1945>),

Title: Discrimination of Alternate Reproductive Tactics (ARTs).
Author: J. Mark Rowland, Clifford Qualls, and Christian Gunning
Description: This package computes the maximum likelihood estimate of a
mixture of distributions of a measured ARTs trait.  Supported
distributions include a mix of 2 normals and a mix of 2 facing

Title: Discrimination of Alternative Reproductive Tactics (ARTs).
Description: 'discrimARTs' discriminates with explicit confidence the alternative reproductive tactics (ARTs) in dimorphic systems with bimodal traits by computing the maximum likelihood estimate of a mixture of distributions of a measured ARTs trait. Supported distributions include a mixture of 2 normal distributions and a mixture of 2 facing gamma distributions.