From 3ce24659238e9afcffdee00177c535125f22981c Mon Sep 17 00:00:00 2001 From: Gertjan van den Burg Date: Mon, 9 Mar 2020 16:26:00 +0000 Subject: Minor improvements to readme --- README.md | 61 ++++++++++++++++++++++++++++++++++++++----------------------- 1 file changed, 38 insertions(+), 23 deletions(-) diff --git a/README.md b/README.md index 918afc2..d62a060 100644 --- a/README.md +++ b/README.md @@ -1,19 +1,22 @@ -GenSVM C Package -================ +GenSVM +====== -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). +This is the repository for the C implementation of *GenSVM*, a generalized +multiclass support vector machine proposed in: -GitHub: -[https://github.com/GjjvdBurg/GenSVM](https://github.com/GjjvdBurg/GenSVM) +> [GenSVM: A Generalized Multiclass Support Vector +> Machine](http://jmlr.org/papers/v17/14-526.html)
+> G.J.J. van den Burg and P.J.F. Groenen
+> *Journal of Machine Learning Research*, 2016. -GenSVM is also available in these languages: +GenSVM is available in these languages: Language | URL :-------:|:-------: | [https://github.com/GjjvdBurg/PyGenSVM](https://github.com/GjjvdBurg/PyGenSVM) | [https://github.com/GjjvdBurg/RGenSVM](https://github.com/GjjvdBurg/RGenSVM) + | [https://github.com/GjjvdBurg/GenSVM](https://github.com/GjjvdBurg/GenSVM) + Introduction ------------ @@ -55,14 +58,18 @@ in the Makefile. Then, compile the library with a simple: - make +``` +$ make +``` If you like to run the tests, use ``make test`` on the command line. After successful compilation, you will have two executables ``gensvm`` and ``gensvm_grid``. Type: - ./gensvm +``` +$ ./gensvm +``` To get an overview of the command line options to the executable (similar for ``gensvm_grid``). @@ -74,7 +81,9 @@ executable can be used to run a grid search on a dataset. Here's an example of using the ``gensvm`` executable on a single dataset, with some custom parameters: - ./gensvm -l 1e-5 -k 1.0 -p 1.5 data/iris.train +``` +$ ./gensvm -l 1e-5 -k 1.0 -p 1.5 data/iris.train +``` This fits the model with regularization parameter ``1e-5``, Huber hinge parameter ``1.0`` and lp norm parameter ``1.5``, and default settings @@ -99,12 +108,16 @@ independent measurements of training time. Here's an example of running ``gensvm_grid`` without repeats on the iris dataset: - ./gensvm_grid training/iris_norepeats.training +``` +$ ./gensvm_grid training/iris_norepeats.training +``` On my computer this runs in about 8 seconds with 342 hyperparameter configurations. Alternatively, if consistency checks are desired we can run: - ./gensvm_grid training/iris.training +``` +$ ./gensvm_grid training/iris.training +``` which runs the same grid search but also does 5 consistency repeats for each of the configurations with the 5% best performance. Note that the performance @@ -119,16 +132,18 @@ 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} - } +```bib +@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