Machine learning in the mineral resource sector: An overview
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Authors
Cevik, S. Ilkay
Ortiz, Julian M.
Date
2020
Type
preprint
Language
en
Keyword
Alternative Title
Abstract
The increasing availability of the large and high-resolution geoscience data sets challenges the pattern recognition abilities of geoscientists. Machine learning algorithms provide opportunities to extend these pattern recognition abilities into high dimensional, large data sets. In this paper we present an overview of the commonly used supervised and unsupervised machine learning methods that are available for a geoscientist, and their use. A generic workflow is also provided, along with a review of several case studies, to present an overview of the state-of-the-art applications.
Description
Citation
Cevik SI, Ortiz JM (2020) Machine learning in the mineral resource sector: An overview, paper 2020-07-01. Preprint.
Publisher
Queen's University