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Learning to Predict Forest Fires With Different Data Mining Techniques

Category: Data Management

Tags: data mining, data

Overview The motive for this paper was to learn to predict forest fires in Slovenia using different data mining techniques. They used predictive models based on the forest structure GIS (Geographical Information System), the weather prediction model - Aladin and MODIS satellite data. They examined three different datasets: one for the Kras region, one for Primorska region and one for continental Slovenia because of the climate differences. On these datasets they applied logistic regression and decision trees (J48), as well as random forests, bagging and boosting of decision trees, in order to obtain predictive models of fire occurrence. Best results in terms of predictive accuracy were obtained by bagging decision trees.

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Publisher
Jozef Stefan Institute
File Format
PDF
Date Published
Oct 1, 2008
Format
White Papers
Topics
Knowledge and Data Management, Data Mining - Analysis

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