~ These files are distributed under the "GNU GENERAL PUBLIC LICENSE" (contained in file LICENSE). ~ Authors: Michele Donini and Fabio Aiolli ~ Citation Request: Use of this code in publications should be acknowledged by referencing the following publication: "EasyMKL: a scalable multiple kernel learning algorithm by Fabio Aiolli and Michele Donini, Neurocomputing, 2015" @article{aiolli2015easymkl, title={EasyMKL: a scalable multiple kernel learning algorithm}, author={Aiolli, Fabio and Donini, Michele}, journal={Neurocomputing}, year={2015}, publisher={Elsevier} } ~ Site: http://www.math.unipd.it/~mdonini/publications.html = = = Python Folder = = = ~ Required Python packages numpy scikit-learn cvxopt ---------------------------------------------------------------------------------------------------- File Content EasyMKL.py EasyMKL implementation komd.py Scikit-like implementation of the kernel machine KOMD toytest_EasyMKL.py An example of EasyMKL toytest_komd.py An example of KOMD komd_gui.py Graphical toytest interface for KOMD = = = R Folder = = = ~ Required R package kernlab ---------------------------------------------------------------------------------------------------- File Content komd.R R implementation of the kernel machine KOMD with a toy example