Abstract--Many studies have shown the limits of support/confidence framework used in Apriori-like algorithms to mine association rules. One solution to cope with this limitation is...
Yannick Le Bras, Philippe Lenca, Sorin Moga, St&ea...
Beam search is used to maintain tractability in large search spaces at the expense of completeness and optimality. We study supervised learning of linear ranking functions for con...
It is often expensive to acquire data in real-world data mining applications. Most previous data mining and machine learning research, however, assumes that a fixed set of trainin...
The general dimension is a combinatorial measure that characterizes the number of queries needed to learn a concept class. We use this notion to show that any p-evaluatable concep...
Anomaly detection for network intrusion detection is usually considered an unsupervised task. Prominent techniques, such as one-class support vector machines, learn a hypersphere ...