Clustering of large data bases is an important research area with a large variety of applications in the data base context. Missing in most of the research efforts are means for g...
Alexander Hinneburg, Daniel A. Keim, Markus Wawryn...
This paper presents an approach for classifying students in order to predict their final grade based on features extracted from logged data in an education web-based system. A comb...
This paper describes an evolutionary clustering algorithm, which can partition a given dataset automatically into the optimal number of groups through one shot of optimization. The...
This paper presents an efficient hybrid feature selection model based on Support Vector Machine (SVM) and Genetic Algorithm (GA) for large healthcare databases. Even though SVM an...
Rick Chow, Wei Zhong, Michael Blackmon, Richard St...
Kernel functions can be viewed as a non-linear transformation that increases the separability of the input data by mapping them to a new high dimensional space. The incorporation ...