An Unsupervised Fuzzy Classification Algorithm for Non Elliptic Classes

Author(s):  
P. Billaudel ◽  
A. Devillez ◽  
G. Villermain Lecolier
1994 ◽  
Vol 16 (5) ◽  
pp. 161-165
Author(s):  
D. J. Ramsbottom ◽  
M. J. Adams ◽  
J. Carroll

The classification of polymer samples from their infra-red spectra has been achieved by the application of a fuzzy c-means cluster algorithm. The generation of a fuzzy classifier allows the characterization of samples which are a combination of more than one pure polymer.


2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Cailing Li ◽  
Wenjun Li

In order to realize efficient data processing in wireless network, this paper designs an automatic classification algorithm of multisearch data association rules in a wireless network. According to the algorithm, starting from the mining of multisearch data association rules, from the discretization of continuous attributes of multisearch data, generation of fuzzy classification rules, and the design of association rule classifier and other aspects, automatic classification is completed by using the mining results. Experimental results show that this algorithm has the advantages of small classification error, good real-time performance, high coverage rate, and high feasibility.


2017 ◽  
Vol 58 ◽  
Author(s):  
Aleksandras Krylovas ◽  
Natalja Kosareva ◽  
Julija Karaliūnaitė

In the article one fuzzy classification algorithm of dichotomous test questions is proposed. Depending on the level of knowledge measured by the test, the test item for example may well differentiate whether all testees or only testees with strong or only with weak level of knowledge; as well as the test item may badly differentiate testees and therefore be inappropriate. In the research fuzzy sets mathematical theory is used.


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