Information-theoretic clustering aims to exploit information theoretic measures as the clustering criteria. A common practice on this topic is so-called INFO-K-means, which perfor...
Given its importance, the problem of predicting rare classes in large-scale multi-labeled data sets has attracted great attentions in the literature. However, the rare-class probl...
Constructive Induction is the process of transforming the original representation of hard concepts with complex interaction into a representation that highlights regularities. Mos...
Exploratory data analysis is a process of sifting through data in search of interesting information or patterns. Analysts’ current tools for exploring data include database mana...
Multi-label learning arises in many real-world tasks where an object is naturally associated with multiple concepts. It is well-accepted that, in order to achieve a good performan...