Running Data Grid applications such as High Energy Nuclear Physics (HENP) and weather modelling experiments involves working with huge data sets possibly of hundreds of Terabytes ...
The crucial issue in many classification applications is how to achieve the best possible classifier with a limited number of labeled data for training. Training data selection is ...
In this study, a hybrid intelligent data mining methodology, genetic algorithm based support vector machine (GASVM) model, is proposed to explore stock market tendency. In this hyb...
Abstract--Imbalanced data sets present a particular challenge to the data mining community. Often, it is the rare event that is of interest and the cost of misclassifying the rare ...
Existing association rule mining algorithms suffer from many problems when mining massive transactional datasets. Some of these major problems are: (1) the repetitive I/O disk sca...