Abstract
In this work we present a study on the analysis of a large data set from seismology. A set of different large margin classifiers based on the well-known support vector machine (SVM) algorithm is used to classify the data into two classes based on their magnitude on the Richter scale. Due to the imbalance of nature between the two classes reweighing techniques are used to show the importance of reweighing algorithms. Moreover, we present an incremental algorithm to explore the possibility of predicting the strength of an earthquake with incremental techniques.
Acknowledgements
The authors thank the editor and the referees for their valuable comments and suggestions that resulted in improving the quality of presentation of this manuscript. The research of the first author (K.D.) was financially supported by a scholarship awarded by Captain Fanourakis Foundation and State Scholarships Foundation.