Model selection in unsupervised learning is a hard problem. In this paper a simple selection criterion for hyperparameters in one-class classifiers (OCCs) is proposed. It makes us...
A method for learning multivariate time series classifiers by inductive logic programming is presented. Two types of background predicate that are suited for this task are introduc...
We propose a new approach for learning Bayesian classifiers from data. Although it relies on traditional Bayesian network (BN) learning algorithms, the effectiveness of our approa...
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...
Nearest neighbor classifier is a widely-used effective method for multi-class problems. However, it suffers from the problem of the curse of dimensionality in high dimensional spac...
Guo-Jun Zhang, Ji-Xiang Du, De-Shuang Huang, Tat-M...