Learning from imbalanced data, where the number of observations in one class is significantly larger than the ones in the other class, has gained considerable attention in the machine learning community. Assuming the difficulty in predicting each class is similar, most standard classifiers will...

Automatic environmental monitoring networks enforced by wireless communication technologies provide large and ever increasing volumes of data nowadays. The use of this information in natural hazard research is an important issue. Particularly useful for risk assessment and decision making are...

The training of Support Vector Machines may be a very difficult task when dealing with very large datasets. The memory requirement and the time consumption of the SVMs algorithms grow rapidly with the increase of the data. To overcome these drawbacks a lot of parallel algorithms have been...