Within a class-labeled dataset, there are typically two or more possible class labels. Class-specific subsets of the dataset have the same class label for each record. Class-specific clusters are the groups of similar records within these subsets. There exists many machine learning techniques which require class-specific clusters. We propose RBClust, a rule based method for finding class-specific clusters. We demonstrate that when compared to traditional clustering methods, the proposed method achieves better cluster quality, and computation time is significantly lower.
|Title of host publication||ESANN 2016|
|Subtitle of host publication||24th European symposium on artificial neural networks, computational intelligence and machine learning, proceedings|
|Place of Publication||Belgium|
|Publisher||European Symposium on Artificial Neural Networks (ESANN)|
|Number of pages||6|
|ISBN (Electronic)||9782875870278, 9782875780270|
|Publication status||Published - 2016|
|Event||24th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning - Novotel hotel , Bruges, Belgium|
Duration: 27 Apr 2016 → 29 Apr 2016
https://web.archive.org/web/20160314003553/https://www.elen.ucl.ac.be/esann/ (Conference website)
https://www.esann.org/esann16programme (Conference program)
|Conference||24th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning|
|Period||27/04/16 → 29/04/16|
|Other||The 24 th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning will take place in Bruges, Belgium from 27 to 29 April 2016 .|
This event builds upon a very successful series of conference organized each year since 1993. ESANN has become a major scientific events in the machine learning, computational intelligence and artificial neural networks fields over the years.
The two main tracks are "Theory and methods", and "Information processing and applications". In addition, a number of special sessions will be organized, on selected hot topics in the machine learning, computational intelligence and artificial neural networks fields.