  Causal Learner is a toolbox for learning causal structure and Markov blanket
(MB) from data. It integrates functions for generating simulated Bayesian
network data, a set of state-of-the-art global causal structure learning
algorithms, a set of state-of-the-art local causal structure learning
algorithms, a set of state-of-the-art MB learning algorithms, and functions for
evaluating algorithms. The data generation part of Causal Learner is written in
R, and the rest of Causal Learner is written in MATLAB. Causal Learner aims to
provide researchers and practitioners with an open-source platform for causal
learning from data and for the development and evaluation of new causal
learning algorithms. The Causal Learner project is available at
http://bigdata.ahu.edu.cn/causal-learner.
