Abstract
This document describes an approach to the prob-lem of predicting dangerous seismic events in active coal mines up to 8 hours in advance. It was developed as a part of the AAIA'16 Data Mining Challenge: Predicting Dangerous Seismic Events in Active Coal Mines. The solutions presented consist of ensembles of various predictive models trained on different sets of features. The best one achieved a winning score of 0.939 AUC.
Cite
CITATION STYLE
Bogucki, R., Lasek, J., Milczek, J. K., & Tadeusiak, M. (2016). Early warning system for seismic events in Coal Mines using machine learning. In Proceedings of the 2016 Federated Conference on Computer Science and Information Systems, FedCSIS 2016 (pp. 213–220). Institute of Electrical and Electronics Engineers Inc. https://doi.org/10.15439/2016F420
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