Fair train-test split in machine learning: Mitigating spatial autocorrelation for improved prediction accuracy-Reference-Cited by-同舟云学术

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Fair train-test split in machine learning: Mitigating spatial autocorrelation for improved prediction accuracy

Published:2022-02 Issue: Volume:209 Page:109885
ISSN:0920-4105
Container-title:Journal of Petroleum Science and Engineering
language:en
Short-container-title:Journal of Petroleum Science and Engineering

Author:

Salazar Jose J.^ORCID,Garland Lean,Ochoa Jesus,Pyrcz Michael J.

Funder

University of Texas at Austin

Publisher

Elsevier BV

Subject

Geotechnical Engineering and Engineering Geology,Fuel Technology

Reference42 articles.

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2. Cython: the best of both worlds;Behnel;Comput. Sci. Eng.,2011

3. Spatial cross-validation and bootstrap for the assessment of prediction rules in remote sensing: the R package sperrorest;Brenning,2012

4. Geostatistics: Modeling Spatial Uncertainty;Chilès,2012

5. GSLIB: Geostatistical Software Library and User’s Guide;Deutsch,1998

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