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Performance Prediction Challenge - Models
WCCI Performance Prediction Challenge

The challenge is over, but a new challenge is on-going using the same datasets, check it out!

The Challenge Learning Object package (CLOP)

A Matlab(R) library of models to perform the tasks of the challenge is provided for your convenience. You are not required to use this package, you can write your own code.

Download CLOP

CLOP may be downloaded and used freely for the purposes of the challenge. Please make sure you read the license agreement and the disclaimer. CLOP is based on the Spider developed at the Max Planck Institute for Biological Cybernetics and integrates software from several sources, see the credits. Download CLOP now (beta version, 4.7 MB.)

Installation requirements

CLOP runs with Matlab (Version 12 or greater) using either Linux or Windows.

Installation instructions

Unzip the archive and follow the instructions in the README file. Windows users will just have to run a script to set the Matlab path properly. Unix users will have to compile the LibSVM package if they want to use support vector machines. The Random Forest package is presently not supported under Unix.

Getting started

The sample code provided gives you and easy way of getting started. Consult the CLOP FAQ for further information.

Bugs and improvements

Please report bugs to modelselect@clopinet.com. Suggestions and code improvements are also welcome.

Bonus entries

We have canceled the option to make "bonus entries" using CLOP. This part of the challenge will be replaced by a post-challenge game to be announced.