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Fuzzy K-means

Figure 16 Results of applying the fuzzy k-means clustering algorithm to the data from Table 9. The values in parenthesis indicate the membership function for each object relative to group A... Figure 16 Results of applying the fuzzy k-means clustering algorithm to the data from Table 9. The values in parenthesis indicate the membership function for each object relative to group A...
Despite the advantages of fuzzy k-means clustering, the method has the following limitations ... [Pg.576]

Figure 4.17 Results of appyling the fuzzy k-means clustering algorithm to the data from... Figure 4.17 Results of appyling the fuzzy k-means clustering algorithm to the data from...
Keywords— acute leukemia blood images, clustering. Moving K-means, Fuzzy K-means, saturation component. [Pg.617]

In this study, two clustering algorithms namely Moving K-means and Fuzzy K-means have been used for automated... [Pg.618]

Fuzzy K-means is developed by Dunn in 1973 [16] but improved by Bezdek in 1981 [17]. Fuzzy K-means clustering minimizes the following function as in... [Pg.619]

See other pages where Fuzzy K-means is mentioned: [Pg.116]    [Pg.576]    [Pg.576]    [Pg.122]    [Pg.617]    [Pg.617]    [Pg.617]    [Pg.619]    [Pg.619]    [Pg.619]    [Pg.619]    [Pg.619]    [Pg.620]    [Pg.621]    [Pg.621]    [Pg.621]    [Pg.621]    [Pg.621]    [Pg.621]   
See also in sourсe #XX -- [ Pg.617 ]



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