Enhancing Prediction Performance of Landslide Susceptibility Model Using Hybrid Machine Learning Approach of Bagging Ensemble and Logistic Model Tree

Enhancing Prediction Performance of Landslide Susceptibility Model Using Hybrid Machine Learning Approach of Bagging Ensemble and Logistic Model Tree

The objective of this research is introduce a new machine learning ensemble approach that is a hybridization of Bagging ensemble (BE) and Logistic Model Trees (LMTree), named as BE-LMtree, for improving the performance of the landslide susceptibility model. The LMTree is a relatively new machine lea...

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Bibliographic Details
Main Authors: Xuan Luan Truong, Muneki Mitamura, Yasuyuki Kono, Venkatesh Raghavan, Go Yonezawa, Xuan Quang Truong, Thi Hang Do, Dieu Tien Bui, Saro Lee
Format: Article
Language:English
Published: MDPI AG 2018-06-01
Series:Applied Sciences
Subjects:
landslide
bagging ensemble
Logistic Model Trees
GIS
Vietnam
Online Access:http://www.mdpi.com/2076-3417/8/7/1046

Internet

http://www.mdpi.com/2076-3417/8/7/1046

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