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A comparative study of the use of large margin classifiers on seismic data

Author

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  • Krystallenia Drosou
  • Andreas Artemiou
  • Christos Koukouvinos

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.

Suggested Citation

  • Krystallenia Drosou & Andreas Artemiou & Christos Koukouvinos, 2015. "A comparative study of the use of large margin classifiers on seismic data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(1), pages 180-201, January.
    • Handle: RePEc:taf:japsta:v:42:y:2015:i:1:p:180-201
    DOI: 10.1080/02664763.2014.938619
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