Comparing GIS-based support vector machine kernel functions for landslide susceptibility mapping

Author:

Feizizadeh BakhtiarORCID,Roodposhti Majid Shadman,Blaschke Thomas,Aryal Jagannath

Publisher

Springer Science and Business Media LLC

Subject

General Earth and Planetary Sciences,General Environmental Science

Reference66 articles.

1. Abe S (2010) Two-class support vector machines. In Support vector machines for pattern classification, Advances in Pattern Recognition. Springer, London, pp 21–112

2. Ayalew L, Yamagishi H (2005) The application of GIS-based logistic regression for landslide susceptibility mapping in the Kakuda–Yahiko Mountains, Central Japan. Geomorphology 65(1/2):15–13

3. Bai SB, Wang J, Lu GN, Kanevski M, Pozdnoukhov A (2008) GIS-based landslide susceptibility mapping with comparisons of results from machine learning methods versus logistic regression in basin scale, Geophysical Research Abstracts, EGU, vol. 10, A-06367

4. Bak M (2009) Support vector classifier with linguistic interpretation of the kernel matrix in speaker verification, man-machine interactions, Krzysztof A. Cyran, Stanislaw Kozielski, James F. Peters (eds.), ISSN 1867–5662, Springer, 2009, 399–406

5. Ballabio C, Sterlacchini S (2012) Support vector machines for landslide susceptibility mapping: the Staffora River basin case study, Italy. Math Geosci 44(1):47–70

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