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+GenSVM R Package
+================
+
+This package implements the GenSVM Multiclass Support Vector Machine 
+classifier in R.
+
+![Pretty picture](./.image.png)
+
+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