CLOP is a software package containing several ready-to-use machine learning algorithms which is developed during Performance Prediction Challenge, as a part of Model Selection Workshop in IEEE World Congress on Computational Intelligence, Vancouver, BC, Canada, July 2006. For more information and for related citations, please refer to the following paper:
Isabelle Guyon, Amir Saffari, Gideon Dror, and Joachim Buhmann, Performance Prediction Challenge, In Proceedings of International Conference on Neural Networks (IJCNN), IEEE World Congress on Computational Intelligence (WCCI) 2006, Pages: 2958-2965, Vancouver, British Columbia, Canada, July 2006.
CLOP is based on SPIDER package from Department of Empirical Inference for Machine Learning and Perception, Max Planck Institute for Biological Cybernetics, Tuebingen, Germany. CLOP has more algorithms provided by challenge organizers compared to Spider and it runs on MATLAB, but it does not depend on any particular toolbox of MATLAB. Please feel free to contact us if you had any problem, suggestion, need more information.
Download the latest version from here:
Version 1.0: (Release date: May 17, 2006)