Probabilistic outlier detection for sparse multivariate geotechnical site investigation data using Bayesian learning

Probabilistic outlier detection for sparse multivariate geotechnical site investigation data using Bayesian learning

Various uncertainties arising during acquisition process of geoscience data may result in anomalous data instances (i.e., outliers) that do not conform with the expected pattern of regular data instances. With sparse multivariate data obtained from geotechnical site investigation, it is impossible t...

Full description

Bibliographic Details
Main Authors: Shuo Zheng, Yu-Xin Zhu, Dian-Qing Li, Zi-Jun Cao, Qin-Xuan Deng, Kok-Kwang Phoon
Format: Article
Language:English
Published: Elsevier 2021-01-01
Series:Geoscience Frontiers
Subjects:
Outlier detection
Site investigation
Sparse multivariate data
Mahalanobis distance
Resampling by half-means
Bayesian machine learning
Online Access:http://www.sciencedirect.com/science/article/pii/S1674987120300918

Internet

http://www.sciencedirect.com/science/article/pii/S1674987120300918

Similar Items