A comparative study of different machine learning methods for landslide susceptibility assessment: a case study of Uttarakhand area (India)
Landslide susceptibility assessment of Uttarakhand area of India has been done by applying five machine learning methods namely Support Vector Machines (SVM), Logistic Regression (LR), Fisher's Linear Discriminant Analysis (FLDA), Bayesian Network (BN), and Naïve Bayes (NB). Performance of thes...
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Main Authors: | , , , , |
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Format: | Article |
Language: | English |
Published: |
Elsevier
2016
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Online Access: | http://psasir.upm.edu.my/id/eprint/54823/1/A%20comparative%20study%20of%20different%20machine%20learning%20methods%20for%20landslide%20susceptibility%20assessment%20a%20case%20study%20of%20Uttarakhand%20area%20%28India%29.pdf http://psasir.upm.edu.my/id/eprint/54823/ |
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