diff options
| -rw-r--r-- | .image.png | bin | 0 -> 24251 bytes | |||
| -rw-r--r-- | README.md | 104 |
2 files changed, 104 insertions, 0 deletions
diff --git a/.image.png b/.image.png Binary files differnew file mode 100644 index 0000000..281878c --- /dev/null +++ b/.image.png diff --git a/README.md b/README.md new file mode 100644 index 0000000..65f1f88 --- /dev/null +++ b/README.md @@ -0,0 +1,104 @@ +GenSVM R Package +================ + +This package implements the GenSVM Multiclass Support Vector Machine +classifier in R. + + + +Introduction +------------ + +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 functions that +measures how misclassifications are counted is very flexible. This allows the +user to tune the classifier to the dataset at hand and potentially obtain +higher classification accuracy. Moreover, this flexibility means that +GenSVM has a number of alternative 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. + +For more information about GenSVM, see the paper: [GenSVM: A Generalized +Multiclass Support Vector Machine](http://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). + + +Installation +------------ + +This package can be installed from CRAN: + + install.packages('gensvm') + +Usage +----- + +The package is extensively documented with many examples. See +`?gensvm-package`, `?gensvm` and `?gensvm.grid` in R. + +The main GenSVM functions are: +* `gensvm` : Fit a GenSVM model for specific model parameters. +* `gensvm.grid` : Run a cross-validated grid search for GenSVM. + +Both these functions return S3 objects that for which `plot` and `predict` +functions are available. For the GenSVMGrid object the function is applied to +the best model found during training. For both of these objects a `coef` +function is also available. + +The following utility functions are also included in the package: +* `gensvm.accuracy` : Compute the accuracy score between true and predicted + class labels +* `gensvm.maxabs.scale` : Scale each column of the dataset by its maximum + absolute value, preserving sparsity and mapping the data to [-1, 1] +* `gensvm.train.test.split` : Split a dataset into a training and testing + sample +* `gensvm.refit` : Refit a fitted GenSVM model with slightly different + parameters or on a different dataset + +Citing +------ + +If you use GenSVM in your work, please cite the paper using the information +avialable through the following R command: + + citation('gensvm') + +Alternatively, you can use the following BibTeX code directly: + + @article{JMLR:v17:14-526, + author = {Gerrit J.J. van den Burg and Patrick J.F. Groenen}, + title = {{GenSVM}: A Generalized Multiclass Support Vector Machine}, + journal = {Journal of Machine Learning Research}, + year = {2016}, + volume = {17}, + number = {225}, + pages = {1-42}, + url = {http://jmlr.org/papers/v17/14-526.html} + } + +License +------- + + Copyright 2018, G.J.J. van den Burg. + + RGenSVM is free software: you can redistribute it and/or modify + it under the terms of the GNU General Public License as published by + the Free Software Foundation, either version 3 of the License, or + (at your option) any later version. + + RGenSVM is distributed in the hope that it will be useful, + but WITHOUT ANY WARRANTY; without even the implied warranty of + MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the + GNU General Public License for more details. + + You should have received a copy of the GNU General Public License + along with RGenSVM. If not, see <http://www.gnu.org/licenses/>. + + For more information please contact: + + G.J.J. van den Burg + email: gertjanvandenburg@gmail.com |
