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Lithologic mapping using Random Forests applied to geophysical and remote sensing data: a demonstration study from the Eastern Goldfields of Australia

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Figure

Figure 1. Schematic representation of the Yilgarn Craton including the location of majorgold deposits
Figure 2. Schematic geology of the St. Ives gold camp including the location and extentof the project (red outline box) relative to several major existing and historical gold mines(indicated by red circles with the mine name adjacent)
Figure 3. Heron South geology map. In subsequent figures, the litho-logic units will be abbreviated as follows: Volcanogenic Sediments(VS), Tripod Hill Komatiite (THK), Paringa Basalt (PB), Granitoid(G), High MgO Basalt (HMgOB), Basalt (B), Dolerite 1 (D1)
Figure 4. An example showing three levels of a classification tree, showing at eachnode: (a) the most numerous class, (b) the proportion of samples of the most numerousclass, relative to all samples in the node (shown as percentage and count of total), (c) thepie-graph distribution of all classes present, (d) the variable used to split the parent nodeinto child nodes, and (e) the threshold at which that split was executed.
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