From 7e74c1d813625eb7b0139531fbde3c96a4c55d9e Mon Sep 17 00:00:00 2001 From: Gertjan van den Burg Date: Fri, 30 Dec 2016 18:34:53 +0100 Subject: update links in readme --- README.md | 56 +++++++++++++++++++++++++++++++++++++++----------------- 1 file changed, 39 insertions(+), 17 deletions(-) diff --git a/README.md b/README.md index a1e04b0..4bd06e2 100644 --- a/README.md +++ b/README.md @@ -12,16 +12,26 @@ This is the C library for the GenSVM method. GenSVM is a general multiclass support vector machine, which you can use for classification problems with multiple classes. Training GenSVM in cross-validation or grid search setups can be done efficiently due to the ability to use warm starts. See the -[paper]() for more information, and Usage below for how to use GenSVM. +[paper](http://jmlr.org/papers/v17/14-526.html) for more information, and +Usage below for how to use GenSVM. -The library has support for datasets in [MSVMpack]() and [LibSVM/SVMlight]() -format, and can take advantage of sparse datasets. There is also (preliminary) -support for nonlinear GenSVM through kernels. +The library has support for datasets in +[MSVMpack](https://members.loria.fr/FLauer/files/MSVMpack/MSVMpack.html) and +[LibSVM/SVMlight](https://www.csie.ntu.edu.tw/~cjlin/libsvm/) format, and can +take advantage of sparse datasets. There is also support for nonlinear GenSVM +through kernels. For documentation on how the library is implemented, see the Doxygen -documentation available [here](). There are also many unit tests, which you -can use to further understand how the library works. Test coverage for the -current version is reported [here](). +documentation available [here](https://gjjvdburg.github.io/gensvm/). There are +also many unit tests, which you can use to further understand how the library +works. Test coverage for the current version is reported +[here](https://gjjvdburg.github.io/gensvm/cover). + +This is the C library for GenSVM, which contains two executables for using the +method. Python and R packages for GenSVM are planned. If you are interested in +these, please express your interest for the Python package +[here](https://github.com/GjjvdBurg/GenSVM/issues/1) and for the R package +[here](https://github.com/GjjvdBurg/GenSVM/issues/2). Usage ----- @@ -67,13 +77,14 @@ specified with the ``-o`` option. The ``gensvm_grid`` executable can be used to run a grid search on a dataset. The input to this executable is a file (called a grid file), which specifies the values of the parameters. See the ``training`` directory for examples and -the documentation [here]() for more info on the file format. One important -thing to note is that when the ``repeats`` field has a positive value, a -so-called "consistency check" will be performed after the grid search has -finished. This is a robustness check on the best performing configurations, to -find the best overall hyperparameter configuration with the best performance -and smallest training time. In this robustness check warm-starts are not used, -to ensure the observations are independent measurements of training time. +the documentation [here](https://gjjvdburg.github.io/gensvm/) for more info on +the file format. One important thing to note is that when the ``repeats`` +field has a positive value, a so-called "consistency check" will be performed +after the grid search has finished. This is a robustness check on the best +performing configurations, to find the best overall hyperparameter +configuration with the best performance and smallest training time. In this +robustness check warm-starts are not used, to ensure the observations are +independent measurements of training time. Here's an example of running ``gensvm_grid`` without repeats on the iris dataset: @@ -94,9 +105,20 @@ Reference --------- If you use GenSVM in any of your projects, please cite the GenSVM paper -available at [link](link). You can use the following BibTeX code: - - bibtex here +available at +[http://jmlr.org/papers/v17/14-526.html](http://jmlr.org/papers/v17/14-526.html). +You can use the following BibTeX code: + + @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 ------- -- cgit v1.2.3