Causal Learner: A Toolbox for Causal Structure and Markov Blanket Learning

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 atthis http URL.

@article{ling2025_2103.06544,
  title={ Causal Learner: A Toolbox for Causal Structure and Markov Blanket Learning },
  author={ Zhaolong Ling and Kui Yu and Yiwen Zhang and Lin Liu and Jiuyong Li },
  journal={arXiv preprint arXiv:2103.06544},
  year={ 2025 }
}