User-Friendly R Package for Supervised Machine Learning
Pipelines
c(
person(given = "Begüm",
family = "Topçuoğlu",
role = c("aut"),
email = "topcuoglu.begum@gmail.com",
comment = c(ORCID = "0000-0003-3140-537X")
),
person(given = "Zena",
family = "Lapp",
role = c("aut"),
email = "zenalapp@umich.edu",
comment = c(ORCID = "0000-0003-4674-2176")
),
person(given = "Kelly",
family = "Sovacool",
role = c("aut", "cre"),
email = "sovacool@umich.edu",
comment = c(ORCID = "0000-0003-3283-829X")
),
person(given = "Evan",
family = "Snitkin",
role = c('aut'),
comment = c(ORCID = "0000-0001-8409-278X")),
person(given = "Jenna",
family = "Wiens",
role = c('aut'),
comment = c(ORCID = "0000-0002-1057-7722")),
person(given = "Patrick",
family = "Schloss",
role = c('aut'),
email = 'pschloss@umich.edu',
comment = c(ORCID = "0000-0002-6935-4275")),
person(given = "Nick",
family = "Lesniak",
role = c("ctb"),
email = "nlesniak@umich.edu",
comment = c(ORCID = "0000-0001-9359-5194")))
An interface to build machine learning models for classification
and regression problems. 'mikropml' implements the ML pipeline described
by Topçuoğlu et al. (2020) <doi:10.1128/mBio.00434-20> with reasonable
default options for data preprocessing, hyperparameter tuning,
cross-validation, testing, model evaluation, and interpretation steps.
See the website <http://www.schlosslab.org/mikropml/> for more information,
documentation, and examples.
caret, dplyr, e1071, glmnet, kernlab, MLmetrics, randomForest,
rlang, stats, utils, xgboost
doFuture, foreach, future, future.apply, ggplot2, knitr,
purrr, rmarkdown, rpart, testthat, tidyr

caret, dplyr, e1071, glmnet, kernlab, MLmetrics, randomForest,
rlang, rpart, stats, utils, xgboost
doFuture, foreach, future, future.apply, ggplot2, knitr,
purrr, rmarkdown, testthat, tidyr

c(
person(given = "Begüm",
family = "Topçuoğlu",
role = c("aut"),
email = "topcuoglu.begum@gmail.com",
comment = c(ORCID = "0000-0003-3140-537X")
),
person(given = "Zena",
family = "Lapp",
role = c("aut"),
email = "zenalapp@umich.edu",
comment = c(ORCID = "0000-0003-4674-2176")
),
person(given = "Kelly",
family = "Sovacool",
role = c("aut", "cre"),
email = "sovacool@umich.edu",
comment = c(ORCID = "0000-0003-3283-829X")
),
person(given = "Evan",
family = "Snitkin",
role = c('aut'),
comment = c(ORCID = "0000-0001-8409-278X")),
person(given = "Jenna",
family = "Wiens",
role = c('aut'),
comment = c(ORCID = "0000-0002-1057-7722")),
person(given = "Patrick",
family = "Schloss",
role = c('aut'),
email = 'pschloss@umich.edu',
comment = c(ORCID = "0000-0002-6935-4275")),
person(given = "Nick",
family = "Lesniak",
role = c("ctb"),
email = "nlesniak@umich.edu",
comment = c(ORCID = "0000-0001-9359-5194")),
person(given = "Courtney",
family = "Armour",
role = c("ctb"),
email = "armourc@umich.edu",
comment = c(ORCID = "0000-0002-5250-1224")))
doFuture, foreach, future, future.apply, ggplot2, knitr,
progress, progressr, purrr, rmarkdown, testthat, tidyr