Decision tree induction algorithms scale well to large datasets for their univariate and divide-and-conquer approach. However, they may fail in discovering effective knowledge when...
Giovanni Giuffrida, Wesley W. Chu, Dominique M. Ha...
We investigate the problem of reasoning with partitions of related logical axioms. Our motivation is two-fold. First, we are concerned with how to reason effectively with multiple...
We propose and analyze a distribution learning algorithm for a subclass of Acyclic Probabilistic Finite Automata (APFA). This subclass is characterized by a certain distinguishabi...
Conservation of information (COI) popularized by the no free lunch theorem is a great leveler of search algorithms, showing that on average no search outperforms any other. Yet in ...
This paper examines the induction of classification rules from examples using real-world data. Real-world data is almost always characterized by two features, which are important ...