Lynx is a research-oriented MATLAB toolbox for designing in a fast way supervised machine learning experiments. Details of a simulation can be specified under a configuration file, and the toolbox takes charge of loading data, partitioning it, testing the algorithms and visualizing the results. Additionally, it has support for parallelizing the experiments, and enabling GPU support. This makes large experiments easily repeatable and modifiable.
We have currently pre-implemented several algorithms (e.g. support vector machines, kernel ridge regression...), optimization routines (grid-search procedures, searching the optimal feature subset...), and datasets.
You can see examples of use (taken from my research papers) on:
Please do not hesitate to contact me for any help. Problems and bugs can be reported also on the GitHub page where I will try to answer daily. The toolbox has been tested from MATLAB R2013a up to MATLAB R2015a.
Re-updated description linking to GitHub bug report.
I have updated the description of the toolbox.
Inspired by: Useful Figure Management Utilities, CATSTRUCT, statusbar, Precision-Recall and ROC Curves, Sampling from a discrete distribution, cprintf - display formatted colored text in the Command Window, disptable - Display matrix with column or row labels, Text progress bar, DataHash