Predicting Wildfires

Propositional and Relational Spatio-Temporal Pre-processing Approaches

Mariana Oliveira, Luís Torgo, Vítor Santos Costa
January, 2016
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Abstract

We present and evaluate two different methods for building spatio-temporal features: a propositional method and a method based on propositionalisation of relational clauses. Our motivating application, a regression problem, requires the prediction of the fraction of each Portuguese parish burnt yearly by wildfires–a problem with a strong socio-economic and environmental impact in the country. We evaluate and compare how these methods perform individually and combined together. We successfully use under-sampling to deal with the high skew in the data set. We find that combining the approaches significantly improves the similar results obtained by each method individually.

Type
Conference paper
Publication
Proceedings of the 19th International Conference on Discovery Science
dependent-data spatiotemporal-data environmental-monitoring imbalanced-data
Mariana Oliveira
Mariana Oliveira
Post-doctoral Fellow

Mariana Oliveira is a post-doctoral fellow at Dalhousie University, Faculty of Computer Science. Her research focuses on Machine Learning and Data Mining.