Use bibtex for references (#35)

mlr-org · Sep 30, 2019 · 6a07595 · 6a07595
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diff --git a/DESCRIPTION b/DESCRIPTION
@@ -37,10 +37,11 @@ Depends:
 Imports:
     data.table,
     mlr3 (>= 0.1.3-9000),
-    mlr3misc,
+    mlr3misc (>= 0.1.5),
     paradox,
     R6
 Suggests:
+    bibtex,
     checkmate,
     DiceKriging,
     e1071,
@@ -52,6 +53,7 @@ Suggests:
     testthat,
     withr,
     xgboost
+RdMacros: mlr3misc
 Remotes: mlr-org/mlr3
 Encoding: UTF-8
 NeedsCompilation: no

diff --git a/R/LearnerClassifGlmnet.R b/R/LearnerClassifGlmnet.R
@@ -16,10 +16,7 @@
 #' Calls [glmnet::cv.glmnet()] from package \CRANpkg{glmnet}.
 #'
 #' @references
-#' Jerome Friedman, Trevor Hastie, Robert Tibshirani (2010).
-#' Regularization Paths for Generalized Linear Models via Coordinate Descent.
-#' Journal of Statistical Software, 33(1), 1-22.
-#' \doi{10.18637/jss.v033.i01}.
+#' \cite{mlr3learners}{friedman_2010}
 #'
 #' @export
 #' @template seealso_learner

diff --git a/R/LearnerClassifKKNN.R b/R/LearnerClassifKKNN.R
@@ -16,15 +16,11 @@
 #' Calls [kknn::kknn()] from package \CRANpkg{kknn}.
 #'
 #' @references
-#' Klaus Hechenbichler, Klaus Schliep (2004).
-#' Weighted k-nearest-neighbor techniques and ordinal classification.
-#' Discussion Paper 399, SFB 386, Ludwig-Maximilians University Munich
-#' \doi{10.5282/ubm/epub.1769}
+#' \cite{mlr3learners}{hechenbichler_2004}
 #'
-#' Thomas Cover and Peter Hart (1967).
-#' Nearest neighbor pattern classification.
-#' IEEE transactions on information theory 13.1: 21-27.
-#' \doi{10.1109/TIT.1967.1053964}
+#' \cite{mlr3learners}{samworth_2012}
+#'
+#' \cite{mlr3learners}{cover_1967}
 #'
 #' @export
 #' @template seealso_learner

diff --git a/R/LearnerClassifLDA.R b/R/LearnerClassifLDA.R
@@ -16,10 +16,7 @@
 #' Calls [MASS::lda()] from package \CRANpkg{MASS}.
 #'
 #' @references
-#' William N. Venables, Brian D. Ripley (2002).
-#' Modern Applied Statistics with S.
-#' Fourth Edition. Springer, New York. ISBN 0-387-95457-0.
-#' \doi{10.1007/978-0-387-21706-2}.
+#' \cite{mlr3learners}{venables_2002}
 #'
 #' @export
 #' @template seealso_learner

diff --git a/R/LearnerClassifQDA.R b/R/LearnerClassifQDA.R
@@ -16,10 +16,7 @@
 #' Calls [MASS::qda()] from package \CRANpkg{MASS}.
 #'
 #' @references
-#' William N. Venables, Brian D. Ripley (2002).
-#' Modern Applied Statistics with S.
-#' Fourth Edition. Springer, New York. ISBN 0-387-95457-0.
-#' \doi{10.1007/978-0-387-21706-2}.
+#' \cite{mlr3learners}{venables_2002}
 #'
 #' @export
 #' @template seealso_learner

diff --git a/R/LearnerClassifRanger.R b/R/LearnerClassifRanger.R
@@ -16,15 +16,9 @@
 #' Calls [ranger::ranger()] from package \CRANpkg{ranger}.
 #'
 #' @references
-#' Marvin N. Wright, Andreas Ziegler (2017).
-#' ranger: A Fast Implementation of Random Forests for High Dimensional Data in C++ and R.
-#' Journal of Statistical Software, 77(1), 1-17.
-#' \doi{10.18637/jss.v077.i01}.
+#' \cite{mlr3learners}{wright_2017}
 #'
-#' Breiman, L. (2001).
-#' Random Forests.
-#' Machine Learning 45(1).
-#' \doi{10.1023/A:1010933404324}.
+#' \cite{mlr3learners}{breiman_2001}
 #'
 #' @export
 #' @template seealso_learner

diff --git a/R/LearnerClassifSVM.R b/R/LearnerClassifSVM.R
@@ -15,9 +15,7 @@
 #' A learner for a classification support vector machine implemented in [e1071::svm()].
 #'
 #' @references
-#' Corinna Cortes, Vladimir Vapnik (1995).
-#' Machine Learning 20: 273.
-#' \doi{10.1007/BF00994018}.
+#' \cite{mlr3learners}{cortes_1995}
 #'
 #' @export
 #' @template seealso_learner

diff --git a/R/LearnerClassifXgboost.R b/R/LearnerClassifXgboost.R
@@ -16,10 +16,7 @@
 #' Calls [xgboost::xgb.train()] from package \CRANpkg{xgboost}.
 #'
 #' @references
-#' Tianqi Chen, Carlos Guestrin (2016).
-#' XGBoost: A Scalable Tree Boosting System.
-#' 22nd SIGKDD Conference on Knowledge Discovery and Data Mining.
-#' \doi{10.1145/2939672.2939785}.
+#' \cite{mlr3learners}{chen_2016}
 #'
 #' @export
 #' @template seealso_learner

diff --git a/R/LearnerRegrGlmnet.R b/R/LearnerRegrGlmnet.R
@@ -17,10 +17,7 @@
 #' Hyperparameter `family` is set to `"gaussian"`.
 #'
 #' @references
-#' Jerome Friedman, Trevor Hastie, Robert Tibshirani (2010).
-#' Regularization Paths for Generalized Linear Models via Coordinate Descent.
-#' Journal of Statistical Software, 33(1), 1-22.
-#' \doi{10.18637/jss.v033.i01}.
+#' \cite{mlr3learners}{friedman_2010}
 #'
 #' @export
 #' @template seealso_learner

diff --git a/R/LearnerRegrKKNN.R b/R/LearnerRegrKKNN.R
@@ -16,15 +16,11 @@
 #' Calls [kknn::kknn()] from package \CRANpkg{kknn}.
 #'
 #' @references
-#' Klaus Hechenbichler, Klaus Schliep (2004).
-#' Weighted k-nearest-neighbor techniques and ordinal classification.
-#' Discussion Paper 399, SFB 386, Ludwig-Maximilians University Munich
-#' \doi{10.5282/ubm/epub.1769}
+#' \cite{mlr3learners}{hechenbichler_2004}
 #'
-#' Thomas Cover and Peter Hart (1967).
-#' Nearest neighbor pattern classification.
-#' IEEE transactions on information theory 13.1: 21-27.
-#' \doi{10.1109/TIT.1967.1053964}
+#' \cite{mlr3learners}{samworth_2012}
+#'
+#' \cite{mlr3learners}{cover_1967}
 #'
 #' @export
 #' @template seealso_learner

diff --git a/R/LearnerRegrKM.R b/R/LearnerRegrKM.R
@@ -21,10 +21,7 @@
 #' * The additional hyperparameter `jitter` can be set to add `N(0, [jitter])`-distributed noise to the data before prediction to avoid perfect interpolation. We recommend a value of `1e-12`.
 #'
 #' @references
-#' Olivier Roustant, David Ginsbourger, Yves Deville (2012).
-#' DiceKriging, DiceOptim: Two R Packages for the Analysis of Computer Experiments by Kriging-Based Metamodeling and Optimization.
-#' Journal of Statistical Software, 51(1), 1-55.
-#' \doi{10.18637/jss.v051.i01}.
+#' \cite{mlr3learners}{roustant_2012}
 #'
 #' @export
 #' @template seealso_learner

diff --git a/R/LearnerRegrRanger.R b/R/LearnerRegrRanger.R
@@ -16,15 +16,9 @@
 #' Calls [ranger::ranger()] from package \CRANpkg{ranger}.
 #'
 #' @references
-#' Marvin N. Wright, Andreas Ziegler (2017).
-#' ranger: A Fast Implementation of Random Forests for High Dimensional Data in C++ and R.
-#' Journal of Statistical Software, 77(1), 1-17.
-#' \doi{10.18637/jss.v077.i01}.
+#' \cite{mlr3learners}{wright_2017}
 #'
-#' Breiman, L. (2001).
-#' Random Forests.
-#' Machine Learning 45(1).
-#' \doi{10.1023/A:1010933404324}.
+#' \cite{mlr3learners}{breiman_2001}
 #'
 #' @export
 #' @template seealso_learner

diff --git a/R/LearnerRegrSVM.R b/R/LearnerRegrSVM.R
@@ -15,9 +15,7 @@
 #' A learner for a regression support vector machine implemented in [e1071::svm()].
 #'
 #' @references
-#' Corinna Cortes, Vladimir Vapnik (1995).
-#' Machine Learning 20: 273.
-#' \doi{10.1007/BF00994018}.
+#' \cite{mlr3learners}{cortes_1995}
 #'
 #' @export
 #' @template seealso_learner

diff --git a/R/LearnerRegrXgboost.R b/R/LearnerRegrXgboost.R
@@ -16,10 +16,7 @@
 #' Calls [xgboost::xgb.train()] from package \CRANpkg{xgboost}.
 #'
 #' @references
-#' Tianqi Chen, Carlos Guestrin (2016).
-#' XGBoost: A Scalable Tree Boosting System.
-#' 22nd SIGKDD Conference on Knowledge Discovery and Data Mining.
-#' \doi{10.1145/2939672.2939785}.
+#' \cite{mlr3learners}{chen_2016}
 #'
 #' @export
 #' @template seealso_learner

diff --git a/inst/references.bib b/inst/references.bib
@@ -0,0 +1,103 @@
+% https://flamingtempura.github.io/bibtex-tidy/
+
+@article{breiman_2001,
+  title        = {Random Forests},
+  author       = {Breiman, Leo},
+  year         = 2001,
+  journal      = {Machine Learning},
+  volume       = 45,
+  number       = 1,
+  pages        = {5--32},
+  doi          = {10.1023/A:1010933404324},
+  issn         = {1573-0565}
+}
+@inproceedings{chen_2016,
+  title        = {Xgboost: A scalable tree boosting system},
+  author       = {Chen, Tianqi and Guestrin, Carlos},
+  year         = 2016,
+  booktitle    = {Proceedings of the 22nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining},
+  pages        = {785--794},
+  doi          = {10.1145/2939672.2939785},
+  organization = {ACM}
+}
+@article{cortes_1995,
+  title        = {Support-vector networks},
+  author       = {Cortes, Corinna and Vapnik, Vladimir},
+  year         = 1995,
+  month        = sep,
+  day          = 1,
+  journal      = {Machine Learning},
+  volume       = 20,
+  number       = 3,
+  pages        = {273--297},
+  doi          = {10.1007/BF00994018}
+}
+@article{cover_1967,
+  title        = {Nearest neighbor pattern classification},
+  author       = {Cover, Thomas and Hart, Peter},
+  year         = 1967,
+  journal      = {IEEE transactions on information theory},
+  publisher    = {IEEE},
+  volume       = 13,
+  number       = 1,
+  pages        = {21--27},
+  doi          = {10.1109/TIT.1967.1053964}
+}
+@article{friedman_2010,
+  title        = {Regularization Paths for Generalized Linear Models via Coordinate Descent},
+  author       = {Jerome Friedman and Trevor Hastie and Robert Tibshirani},
+  year         = 2010,
+  journal      = {Journal of Statistical Software},
+  volume       = 33,
+  number       = 1,
+  pages        = {1--22},
+  doi          = {10.18637/jss.v033.i01}
+}
+@techreport{hechenbichler_2004,
+  title        = {Weighted k-nearest-neighbor techniques and ordinal classification},
+  author       = {Hechenbichler, Klaus and Schliep, Klaus},
+  year         = 2004,
+  number       = {Discussion Paper 399, SFB 386},
+  doi          = {10.5282/ubm/epub.1769},
+  institution  = {Ludwig-Maximilians University Munich}
+}
+@article{roustant_2012,
+  title        = {{DiceKriging}, {DiceOptim}: Two {R} Packages for the Analysis of Computer Experiments by Kriging-Based Metamodeling and Optimization},
+  author       = {Olivier Roustant and David Ginsbourger and Yves Deville},
+  year         = 2012,
+  journal      = {Journal of Statistical Software},
+  volume       = 51,
+  number       = 1,
+  pages        = {1--55},
+  doi          = {10.18637/jss.v051.i01}
+}
+@article{samworth_2012,
+  title        = {Optimal weighted nearest neighbour classifiers},
+  author       = {Samworth, Richard J},
+  year         = 2012,
+  journal      = {The Annals of Statistics},
+  volume       = 40,
+  number       = 5,
+  pages        = {2733--2763},
+  doi          = {10.1214/12-AOS1049}
+}
+@book{venables_2002,
+  title        = {Modern Applied Statistics with S},
+  author       = {W. N. Venables and B. D. Ripley},
+  year         = 2002,
+  publisher    = {Springer},
+  address      = {New York},
+  url          = {http://www.stats.ox.ac.uk/pub/MASS4},
+  note         = {ISBN 0-387-95457-0},
+  edition      = {Fourth}
+}
+@article{wright_2017,
+  title        = {{ranger}: A Fast Implementation of Random Forests for High Dimensional Data in {C++} and {R}},
+  author       = {Wright, Marvin N. and Ziegler, Andreas},
+  year         = 2017,
+  journal      = {Journal of Statistical Software},
+  volume       = 77,
+  number       = 1,
+  pages        = {1--17},
+  doi          = {10.18637/jss.v077.i01}
+}
diff --git a/man/LearnerClassifGlmnet.Rd b/man/LearnerClassifGlmnet.Rd
diff --git a/man/LearnerClassifKKNN.Rd b/man/LearnerClassifKKNN.Rd
diff --git a/man/LearnerClassifLDA.Rd b/man/LearnerClassifLDA.Rd
diff --git a/man/LearnerClassifQDA.Rd b/man/LearnerClassifQDA.Rd
diff --git a/man/LearnerClassifRanger.Rd b/man/LearnerClassifRanger.Rd
diff --git a/man/LearnerClassifSVM.Rd b/man/LearnerClassifSVM.Rd