Explaining anomalies in coal proximity and coal processing data with Shapley and tree-based models
Modelling the characteristics and composition of coal is important, as proximity data and other measurements to do so are typically expensive or hard to acquire in real-time. Understanding anomalies in these relatively small data sets are important, as removal may result in an unnecessary loss of da...
| Main Authors: | , |
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| Format: | Journal Article |
| Language: | English |
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Elsevier
2022
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| Subjects: | |
| Online Access: | http://hdl.handle.net/20.500.11937/97646 |