Classification model based on rough and fuzzy sets theory

Pavel Jirava, Jiří Křupka · Computational intelligence · 2007

The paper reflects the trend of the past years which is based on the diffusion of various traditional approaches and methods to the way of tackling new problems. Two components of the computational intelligence are applied in a classification model. It means rough and fuzzy sets on the basis of which the data classification hybrid model is proposed. It even allows operating with uncertainty data. This model is carried out in MATLAB, and tested on more data files, and compared to others, already known classification methods.

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