WT3.7 – Workshop on Nonstationary Models of Pattern Recognition and Classifier Combinations under the framework
Task Leader: Michał Woźniak, firstname.lastname@example.org
ENGINE research areas: A1, B1-B6
Duration: 1 day
Estimated no. of participants: 25
No. of events: 1
This workshop will be held in the conjunction with the International Conference of Hybrid Artificial Intelligence Systems HAIS. The progress of computer science has caused that many institutions collected huge amount of data, which analysis is impossible by human beings. Nowadays simple methods of data analysis are not sufficient for efficient management of an average enterprise, since for smart decisions the knowledge hidden in data is highly required. The great disadvantage of the aforementioned methods is that they “assume” that statistical properties of the discovered concept (which model is predicted) are being unchanged. In a real situation we could observe the so-called concept drift, therefore designing data mining methods, especially classification ones for data streams is currently the focus of intense research. On the other hand, we can usually use a number of classifiers for each of pattern recognition tasks which differ each other. Therefore developing combined classifiers has been mentioned as ones of the most promising trends in the pattern recognition which can exploit unique elementary classifier strengths and could adapt to the changes of classification models.
The workshop will span through 3 sessions (5 presentation each). There will be a short presentation of the ENGINE Centre at the beginning of each session. For 15 best papers, the ENGINE Centre will reimburse the conference registration fee, if their authors present the paper during the workshop and will participate in the discussion. For all participants of the conference and the ENGINE Centre staff members, the workshop will be free of charge.