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| author | Gertjan van den Burg <gvandenburg@turing.ac.uk> | 2018-04-18 14:35:51 +0100 |
|---|---|---|
| committer | Gertjan van den Burg <gvandenburg@turing.ac.uk> | 2018-04-18 14:35:51 +0100 |
| commit | b3a7675338548a4d084b314bf364b5df2f2dd6ee (patch) | |
| tree | 50c43ee191fd19a1bd80497659771d76310dd946 | |
| parent | update cran-comments with latest check result (diff) | |
| download | rgensvm-b3a7675338548a4d084b314bf364b5df2f2dd6ee.tar.gz rgensvm-b3a7675338548a4d084b314bf364b5df2f2dd6ee.zip | |
Add article url to Description on CRAN request
| -rw-r--r-- | DESCRIPTION | 3 |
1 files changed, 2 insertions, 1 deletions
diff --git a/DESCRIPTION b/DESCRIPTION index e73d82e..152af03 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -16,7 +16,8 @@ Description: The GenSVM classifier is a generalized multiclass support vector the other advantages of GenSVM is that it is trained in the primal 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. + 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>. License: GPL (>= 2) Depends: R (>= 3.0.0) |