Comparison of Support Vector Machine, Bayesian Logistic Regression, and Alternating Decision Tree Algorithms for Shallow Landslide Susceptibility Mapping along a Mountainous Road in the West of Iran

This paper aims to apply and compare the performance of the three machine learning algorithms–support vector machine (SVM), bayesian logistic regression (BLR), and alternating decision tree (ADTree)–to map landslide susceptibility along the mountainous road of the Salavat Abad saddle, Kurdistan prov...

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Principais autores:	Viet-Ha Nhu, Danesh Zandi, Himan Shahabi, Kamran Chapi, Ataollah Shirzadi, Nadhir Al-Ansari, Sushant K. Singh, Jie Dou, Hoang Nguyen
Formato:	Artigo
Idioma:	Inglês
Publicado em:	MDPI AG 2020-07-01
coleção:	Applied Sciences
Assuntos:	shallow landslides machine learning goodness-of-fit support vector machine bayesian logistic regression Kurdistan
Acesso em linha:	https://www.mdpi.com/2076-3417/10/15/5047
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