An outlier is an observation that deviates so much from other observations as to arouse suspicion that it was generated by a different mechanism. Outlier detection has many applic...
Association rule mining is an important data mining problem that has been studied extensively. In this paper, a simple but Fast algorithm for Intersecting attribute lists using a ...
We study the use of kernel subspace methods for learning low-dimensional representations for classification. We propose a kernel pooled local discriminant subspace method and com...
We present an efficient algorithm (UWEP) for updating large itemsets when new transactions are added to the set of old transactions. UWEP employs a dynamic lookahead strategy in u...
Necip Fazil Ayan, Abdullah Uz Tansel, M. Erol Arku...
This paper develops the concept of usefulness in the context of supervised learning. We argue that usefulness can be used to improve the performance of classification rules (as me...
Gholamreza Nakhaeizadeh, Charles Taylor, Carsten L...