


Perform 1D FCM Clustering
[v,U]=Cluster1D(m,x,MaxClusterNo,DimNo,options)
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Parameters
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x - data points column vector. The values should be sorted in ascending
order
MaxClusterNo - the maximum number of clusters
DimNo - the number of the current dimension
options - column vector containing parameters of the FCM clustering
options(1): exponent for the partition matrix U (default: 2.0)
options(2): maximum number of iterations (default: 100)
options(3): minimum amount of improvement (default: 1e-5)
options(4): info display during iteration (default: 0)
options(5): FS index plotting (default: 0)
options(6): indicates whether cluster merging should be done (default: 1)
options(7): indicates whether the clusters should be plotted (default: 0)
options(8): indicates whether the approximated trapezoids should be
plotted (default: 0)
options(9): indicates whether the number of clusters can be reduced to
1 during cluster merging (default: 0)
options(10): similarity treshold for set merging (default: 0.05)
options(11): fuzzy index for the calculation of the FS index
(default: 2)
options(12): cut level for the approximation of the trapezoids
(default: 0.85)
options(13): info display during optimal cluster number determination
(default: 0)
options(14): maximum number of clusters (default: 7)
options(15): number of decimals (default: 2)
options(16): initialization mode of the memebership matrix by
FCM (default: 0('deterministic'))
options(17): treshold for the examination of the identity of two
cluster centers (default:1e-6)
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Returned values
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v - column vector containing the cluster centers
U - matrix containing the membership values
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Remarks
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The optimal number of clusters is determined by the help of the FS
Fukuyama-Sugeno index.
Zsolt Csaba Johanyák, johanyak.csaba@gamf.kefo.hu, v. 1.3, 31. August 2007.