Linear Discriminant Analysis (LDA) is one of the most popular approaches for feature extraction and dimension reduction to overcome the curse of the dimensionality of the high-dime...
Spatial scan statistics are used to determine hotspots in spatial data, and are widely used in epidemiology and biosurveillance. In recent years, there has been much effort invest...
Deepak Agarwal, Andrew McGregor, Jeff M. Phillips,...
The graph classification problem is learning to classify separate, individual graphs in a graph database into two or more categories. A number of algorithms have been introduced fo...
Nikhil S. Ketkar, Lawrence B. Holder, Diane J. Coo...
Multi-label problems arise in various domains such as multitopic document categorization and protein function prediction. One natural way to deal with such problems is to construc...
Clustering is an important technique for understanding and analysis of large multi-dimensional datasets in many scientific applications. Most of clustering research to date has be...