Investor Presentaiton
Validation
For RF the prediction error is assessed by evaluating predictions on the “out-of-bag" data,
which were not used in the training subset.
The testing and the OOB mean squared error are in our case both equal to about 0.2 for winter
season and to 0.17 for summer season, attesting the robustness of the model.
►To assess the methods prediction capabilities, an indipendent dataset (BA 2016-2017) was
employed.
Summer
Winter
% 2016 2017 2016 2017
0.30 0.01 0.04 0.02 0.02
16/01/2017
770 ha
0.20
0.02 0.12 0.02 0.04
0.30
0.11 0.45 0.12 0.16
0.15
0.25 0.22 0.18 0.30
0.05
0.53 0.10 0.39 0.46
CC
0
BY
23/08/2016
322 ha
8 km
WILDFIRE SUSCEPTIBILITY MAPPING IN LIGURIA (ITALY).
17/01/2017
315 ha
Wildfire
Very low
Low
Medium
High
Extreme
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