Meta-learning is an efficient approach in the field of machine learning, which involves multiple classifiers. In this paper, a meta-learning framework consisting of stacking meta-...
Subgroup discovery is the task of identifying the top k patterns in a database with most significant deviation in the distribution of a target attribute Y . Subgroup discovery is ...
Probabilistic inductive logic programming, sometimes also called statistical relational learning, addresses one of the central questions of artificial intelligence: the integratio...
The growing use of information visualization tools and data mining algorithms stems from two separate lines of research. Information visualization researchers believe in the impor...