A complete API client for the image hosting service Imgur.com, including the an imgur graphics device, enabling the easy upload and sharing of plots.

Polish Meteorological and Hydrological Data
c(person(given = "Bartosz",
family = "Czernecki",
role = c("aut", "cre"),
email = "nwp@amu.edu.pl",
comment = c(ORCID = "0000-0001-6496-1386")),
person(given = "Arkadiusz",
family = "Głogowski",
role = "aut"),
person(given = "Jakub",
family = "Nowosad",
role = "aut",
email = "nowosad.jakub@gmail.com",
comment = c(ORCID = "0000-0002-1057-3721")),
person("IMGW-PIB", role = "ctb", comment = "source of the data"))
Download Polish meteorological and hydrological data from the Institute of Meteorology and Water Management - National Research Institute (<https://dane.imgw.pl/>).
This package also allows for adding geographical coordinates for each observation.
Bartosz Czernecki [aut, cre] (<https://orcid.org/0000-0001-6496-1386>),
Arkadiusz Głogowski [aut],
Jakub Nowosad [aut] (<https://orcid.org/0000-0002-1057-3721>),
IMGW-PIB [ctb] (source of the data)

testthat, knitr, rmarkdown, dplyr, tidyr

c(person(given = "Christoph",
family = "Molnar",
role = c("aut", "cre"),
email = "christoph.molnar@gmail.com"),
person(given = "Patrick",
family = "Schratz",
role = "aut",
email = "patrick.schratz@gmail.com",
comment = c(ORCID = "0000-0003-0748-6624")))
Interpretability methods to analyze the behavior
and predictions of any machine learning model.  Implemented methods
are: Feature importance described by Fisher et al. (2018)
<arXiv:1801.01489>, accumulated local effects plots described by Apley
(2018) <arXiv:1612.08468>, partial dependence plots described by
Friedman (2001) <http://www.jstor.org/stable/2699986>, individual
conditional expectation ('ice') plots described by Goldstein et al.
(2013) <doi:10.1080/10618600.2014.907095>, local models (variant of
'lime') described by Ribeiro et. al (2016) <arXiv:1602.04938>, the
Shapley Value described by Strumbelj et. al (2014)
<doi:10.1007/s10115-013-0679-x>, feature interactions described by
Friedman et. al <doi:10.1214/07-AOAS148> and tree surrogate models.
checkmate, data.table, Formula, future, future.apply, ggplot2,
gridExtra, Metrics, prediction, R6
ALEPlot, bench, caret, covr, e1071, future.callr, glmnet,
gower, h2o, keras, knitr, MASS, mlr, mlr3, party, partykit,
patchwork, randomForest, ranger, rmarkdown, rpart, testthat,
yaImpute
Christoph Molnar [aut, cre],
Patrick Schratz [aut] (<https://orcid.org/0000-0003-0748-6624>)