K-means clustering algorithm

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...

Hartigan JA, Wong MA (1979) Algorithm AS 136 A K-means clustering algorithm. J Roy Stat Soc C Appl Stat 28 100-108... 

The k-Means clustering algorithm is used to identify k solutions that are used to create the surrogate models. From the possible m solutions in the archive, k centres pi,..., /xfc are obtained. 

Figure 4.17 Results of appyling the fuzzy k-means clustering algorithm to the data from...

Fisher s Discriminant Ratio in a k-Means Clustering Algorithm for Feature Selection and Data Set Trimming. 

Because of its relationship to SOM, we will describe in greater detail the K-means clustering algorithm. The criterion function is the total squared distance of the data items to their nearest cluster centroids. 

Still, despite the use ofthe K-means clustering algorithm by both techniques of autonomous coordination, each technique differs from the other in terms of whether or not robots rely on any particular member ofthe collective to perform the bulk to the computation required for coordination. The first teclmique presented is that of coordination performed with the hierarchically structured collective. Following that, coordination performed with the horizontally stractuied collective is described. 

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