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| -rw-r--r-- | DESCRIPTION | 4 | ||||
| -rw-r--r-- | README.md | 4 | ||||
| -rw-r--r-- | inst/CITATION | 2 |
3 files changed, 5 insertions, 5 deletions
diff --git a/DESCRIPTION b/DESCRIPTION index dcee490..64c0765 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -18,13 +18,13 @@ Description: The GenSVM classifier is a generalized multiclass support vector space, allowing the use of warm starts during optimization. This means that for common tasks such as cross validation or repeated model fitting, GenSVM can be trained very quickly. Based on: G.J.J. van den - Burg and P.J.F. Groenen (2018) <http://www.jmlr.org/papers/v17/14-526.html>. + Burg and P.J.F. Groenen (2018) <https://www.jmlr.org/papers/v17/14-526.html>. License: GPL (>= 2) Depends: R (>= 3.0.0) Classification/MSC: 62H30, 68T10 URL: https://github.com/GjjvdBurg/RGenSVM - http://jmlr.org/papers/v17/14-526.html + https://jmlr.org/papers/v17/14-526.html BugReports: https://github.com/GjjvdBurg/RGenSVM RoxygenNote: 7.1.0 NeedsCompilation: yes @@ -36,7 +36,7 @@ common tasks such as cross validation or repeated model fitting, GenSVM can be trained very quickly. For more information about GenSVM, see the paper: [GenSVM: A Generalized -Multiclass Support Vector Machine](http://jmlr.org/papers/v17/14-526.html) by +Multiclass Support Vector Machine](https://jmlr.org/papers/v17/14-526.html) by G.J.J. van den Burg and P.J.F. Groenen (*Journal of Machine Learning Research*, 2016). @@ -96,7 +96,7 @@ Alternatively, you can use the following BibTeX code directly: volume = {17}, number = {225}, pages = {1-42}, - url = {http://jmlr.org/papers/v17/14-526.html} + url = {https://jmlr.org/papers/v17/14-526.html} } ``` diff --git a/inst/CITATION b/inst/CITATION index 243ec70..43fcbd9 100644 --- a/inst/CITATION +++ b/inst/CITATION @@ -12,7 +12,7 @@ bibentry(bibtype="article", volume = "17", number = "225", pages = "1-42", - url = "http://jmlr.org/papers/v17/14-526.html", + url = "https://jmlr.org/papers/v17/14-526.html", textVersion = paste( "Gerrit J.J. van den Burg and Patrick J.F. Groenen (2016).", "GenSVM: A Generalized Multiclass Support Vector Machine.", |