AAIA’14 Data Mining Competition
at the Knowledge Pit
AAIA'14 Data Mining Competition:
Key risk factors for Polish State Fire Service was organized within the framework of the 9th International Symposium on Advances in Artificial Intelligence and Applications (AAIA'14), and was an integral part of the 1st Complex Events and Information Modelling workshop (CEIM'14) devoted to the fire protection engeneering. The task was related to the problem of extracting useful knowledge from incident reports obtained from The State Fire Service of Poland. Prizes worth over 3,000 USD were awarded to the most successful teams. The contest was sponsored by Dituel Sp. z o.o. and F&K Consulting Engineers, with a support from The University of Warsaw and ICRA project.
AAIA’14 Data Mining Competition attracted many participants from around the world. In total there were 116 registered teams, from which 57 actively participated in the challenge by submitting at least one solution. We received nearly 1,300 submissions and 46 teams provided a short report describing their approach.
The Data Minining Competition is planned to be continued within the framework of the 10th International Symposium on Advances in Artificial Intelligence and Applications (AAIA'15).
- "Feature Selection for Naive Bayesian Network Ensemble using Evolutionary Algorithms": Adam Zagorecki
- "Robust Method of Sparse Feature Selection for Multi-Label Classification with Naive Bayes": Dymitr Ruta
- "Building an Ensemble from a Single Naive Bayes Classifier in the Analysis of Key Risk Factors for Polish State Fire Service": Stefan Nikolić, Marko Knežević, Vladimir Ivančević, Ivan Luković
- "Identification of Key Risk Factors for the Polish State Fire Service with Cascade Step Forward Feature Selection": Piotr Płoński
- "Feature selection and allocation to diverse subsets for multi-label learning problems with large datasets": Eftim Zdravevski, Petre Lameski, Andrea Kulakov, Dejan Gjorgjevikj
- "Parsimonious Naive Bayes": Marc Boulle