Incorporating Spatial Autocorrelation in Machine Learning Models Using Spatial Lag and Eigenvector Spatial Filtering Features
Applications of machine-learning-based approaches in the geosciences have witnessed a substantial increase over the past few years. Here we present an approach that accounts for spatial autocorrelation by introducing spatial features to the models. In particular, we explore two types of spatial feat...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI
2022
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| Subjects: | |
| Online Access: | View Fulltext in Publisher |