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DESCRIPTION
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Package: cvms
Title: Cross-Validation for Model Selection
Version: 1.6.3.9000
Authors@R:
c(person(given = "Ludvig Renbo",
family = "Olsen",
role = c("aut", "cre"),
email = "[email protected]",
comment = c(ORCID = "0009-0006-6798-7454")),
person(given = "Hugh Benjamin",
family = "Zachariae",
role = "aut"),
person(given = "Indrajeet",
family = "Patil",
role = "ctb",
email = "[email protected]",
comment = c(ORCID = "0000-0003-1995-6531")),
person(given = "Daniel",
family = "Lüdecke",
role = "ctb",
email = "[email protected]",
comment = c(ORCID = "0000-0002-8895-3206")))
Description: Cross-validate one or multiple regression and classification models
and get relevant evaluation metrics in a tidy format. Validate the
best model on a test set and compare it to a baseline evaluation.
Alternatively, evaluate predictions from an external model. Currently
supports regression and classification (binary and multiclass).
Described in chp. 5 of Jeyaraman, B. P., Olsen, L. R.,
& Wambugu M. (2019, ISBN: 9781838550134).
License: MIT + file LICENSE
URL: https://github.com/ludvigolsen/cvms
BugReports: https://github.com/ludvigolsen/cvms/issues
Depends:
R (>= 3.5)
Imports:
checkmate (>= 2.0.0),
data.table (>= 1.12),
dplyr (>= 0.8.5),
ggplot2,
groupdata2 (>= 2.0.5),
lifecycle,
lme4 (>= 1.1-23),
MuMIn (>= 1.43.17),
parameters (>= 0.15.0),
plyr,
pROC (>= 1.16.0),
purrr,
rearrr (>= 0.3.4),
recipes (>= 0.1.13),
rlang (>= 0.4.7),
stats,
stringr,
tibble (>= 3.0.3),
tidyr (>= 1.1.2),
utils
Suggests:
AUC,
covr (>= 3.3.1),
e1071 (>= 1.7-2),
furrr,
ggimage (>= 0.3.3),
ggnewscale (>= 0.5.0),
knitr,
merDeriv (>= 0.2-4),
nnet (>= 7.3-20),
randomForest (>= 4.6-14),
rmarkdown,
rsvg,
testthat (>= 2.3.2),
xpectr (>= 0.4.1)
VignetteBuilder:
knitr
RdMacros:
lifecycle
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.3.2