Learning to Predict Forest Fires with Different Data Mining Techniques
نویسندگان
چکیده
The motivation for this study was to learn to predict forest fires in Slovenia using different data mining techniques. We used predictive models based on data from a GIS (geographical information system), the weather prediction model Aladin and MODIS satellite data. We examined three different datasets: one only for the Kras region, one for whole Primorska region and one for continental Slovenia. On these datasets we applied logistic regression and decision trees, as well as random forests, bagging and boosting of decision trees, in order to obtain predictive models of fire outbrakes. Best results in terms of predictive accuracy were obtained by bagging
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