The license of the PILGRIM platform version, available on this website, is the GNU General Public License (GPL) 3.0.
In the case you want to contribute on this version and send us your code, you must in addition read, sign and send us a copy of the PILGRIM Software Contribution License Agreement (CLA).
The PILGRIM project relies on and encapsulates the ProBT platform, developped by ProbaYes. ProBT allows to model, learn and make inference in Bayesian networks and PILGRIM reuses many of its classes defining basic concepts in probabilistic programming, while extending its capabilities in terms of Bayesian networks structure learning and in terms of relational datasets support.
The ProBT library is distributed with the different PILGRIM projects as a binary file, and is the property of ProbaYes. Using ProBT separately for other purposes is subject to the ProBT licence agreement.
The Database Template Library (DTL) is released under the following copyright :
Copyright © 2002, Michael Gradman and Corwin Joy.
and grants the following permission to its users and updaters :
Permission to use, copy, modify, distribute and sell this software and its documentation for any purpose is hereby granted without fee, provided that the above copyright notice appears in all copies and that both that copyright notice and this permission notice appear in supporting documentation. Corwin Joy and Michael Gradman make no representations about the suitability of this software for any purpose. It is provided « as is » without express or implied warranty.
Shark Machine Learning Library
C++ REST SDK
The GRACLUS graph partitioning library is released under the GNU General Public License (GPL) 3.0.
NMF with KL-divergence (Insight Journal 152)
Some classes also use the work of Pathak et al. in the Insight Journal paper number 152, available under the Creative Commons 3.0 licence with Attribution. This work has been updated by replacing VXL library matrix types and computations by Boost UBLAS ones. In addition, this work has been used as a starting point to implement also other NMF methods.