Meta Learning for Selection of Best Causal Discovery Algorithms

Selection of best causal discovery algorithm for any new dataset is a difficult and time consuming process as it requires a researcher to have prior knowledge about existing standard structure learning algorithms. This research proposed a novel meta-learning approach to this problem. Meta-learning refers to learning about learning algorithms where different kinds of meta-data such as properties of the learning problem performance measures of different algorithms and previous patterns derived fro...See More