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| author | Gertjan van den Burg <gertjanvandenburg@gmail.com> | 2018-04-04 13:34:02 -0400 |
|---|---|---|
| committer | Gertjan van den Burg <gertjanvandenburg@gmail.com> | 2018-04-04 13:34:02 -0400 |
| commit | cf40ee31d0377bbd6b781a2b20066e0b9acac90f (patch) | |
| tree | d36245f157ba2ab7d25fe3441eb3c9d27b2d4011 /DESCRIPTION | |
| parent | fix for weights in refit (diff) | |
| download | rgensvm-cf40ee31d0377bbd6b781a2b20066e0b9acac90f.tar.gz rgensvm-cf40ee31d0377bbd6b781a2b20066e0b9acac90f.zip | |
Update description
Diffstat (limited to 'DESCRIPTION')
| -rw-r--r-- | DESCRIPTION | 19 |
1 files changed, 16 insertions, 3 deletions
diff --git a/DESCRIPTION b/DESCRIPTION index 77509b5..8b13cb1 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -1,15 +1,28 @@ Package: gensvm -Version: 0.0.2 -Date: 2017-07-26 +Version: 0.1.0 +Date: 2018-04-04 Title: GenSVM Authors@R: c(person("Gertjan", "van den Burg", role=c("aut", "cre"), email="gertjanvandenburg@gmail.com"), person("Patrick", "Groenen", email="groenen@ese.eur.nl", role="ctb")) -Description: TBD +Description: The GenSVM classifier is a generalized multiclass support vector + machine (SVM). This classifier aims to find decision boundaries that + separate the classes with as wide a margin as possible. In GenSVM, the + loss function is very flexible in the way that misclassifications are + penalized. This allows the user to tune the classifier to the dataset + at hand and potentially obtain higher classification accuracy than + alternative multiclass SVMs. Moreover, this flexibility means that + GenSVM has a number of other multiclass SVMs as special cases. One of + 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. License: GPL (>= 2) Depends: R (>= 3.0.0) +Classification/MSC: 62H30, 68T10 URL: https://github.com/GjjvdBurg/RGenSVM + https://jmlr.org/papers/v17/14-526.html BugReports: https://github.com/GjjvdBurg/RGenSVM RoxygenNote: 6.0.1 NeedsCompilation: yes |