Optimizing the Predictive Ability of Machine Learning Methods for Landslide Susceptibility Mapping Using SMOTE for Lishui City in Zhejiang Province, China

The main goal of this study was to use the synthetic minority oversampling technique (SMOTE) to expand the quantity of landslide samples for machine learning methods (i.e., support vector machine (SVM), logistic regression (LR), artificial neural network (ANN), and random forest (RF)) to produce hig...

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Detalles Bibliográficos
Autores principales: Wang, Yumiao, Wu, Xueling, Chen, Zhangjian, Ren, Fu, Feng, Luwei, Du, Qingyun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6388203/
https://www.ncbi.nlm.nih.gov/pubmed/30696105
http://dx.doi.org/10.3390/ijerph16030368

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6388203/
https://www.ncbi.nlm.nih.gov/pubmed/30696105
http://dx.doi.org/10.3390/ijerph16030368

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