Clustering is an important data mining problem. Most of the earlier work on clustering focussed on numeric attributes which have a natural ordering on their attribute values. Rece...
Venkatesh Ganti, Johannes Gehrke, Raghu Ramakrishn...
Data reduction makes datasets smaller but preserves classication structures of interest. It is an important area of research in data mining and databases. In this paper we present...
An ensemble is a set of learned models that make decisions collectively. Although an ensemble is usually more accurate than a single learner, existing ensemble methods often tend ...
Background -: Sequencing of EST and BAC end datasets is no longer limited to large research groups. Drops in per-base pricing have made high throughput sequencing accessible to in...
Stephen E. Diener, Thomas D. Houfek, Sam E. Kalat,...
Most known frequent item set mining algorithms work by enumerating candidate item sets and pruning infrequent candidates. An alternative method, which works by intersecting transa...