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Erschienen in:
2015 | OriginalPaper | Buchkapitel
Toward Work Groups Classification Based on Probabilistic Neural Network Approach
verfasst von : Christian Napoli, Giuseppe Pappalardo, Emiliano Tramontana, Robert K. Nowicki, Janusz T. Starczewski, Marcin Woźniak
Erschienen in: Artificial Intelligence and Soft Computing
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This paper presents the application of some Computational Intelligence methods for obtaining a classifier analysing employees to form work groups. The proposed bio-inspired solution analyses employees using data gathered from their professional attitudes and skills, then suggests how to form groups of human resources within a company that can effectively work together. The same proposed tool provides employers with a fair and effective means for employee evaluation. In our approach, employee profiles are processed by a dedicated Radial Basis Probabilistic Neural Network based classifier, which finds non-explicit custom-created groups. The accuracy of the classifier is very high, revealing the potential efficacy of the proposed bio-inspired classification system.