Investor Presentaiton
Variable-class importance
RF allows to measure the relative importance of each variable on the
prediction.
This is obtained by looking at how much the tree nodes, which use that
variable, reduce the mean square errors across all the trees in the
forest.
The vegetation type variable was a categorical one, composed of 37
different classes. The importance of each class is validated through
Partial dependence plots, which give a graphical depiction of the
marginal effect of a single class on the class on the variable importance
on overall susceptibility. Such marginal effect can be positive (class
augmenting fire susceptibility) or negative (class decreasing fire
susceptibility)
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WILDFIRE SUSCEPTIBILITY MAPPING IN LIGURIA (ITALY).
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