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Function Synopsis


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 lyngby_ui_km_init    - GUI for K-means parameter initialization

       function lyngby_ui_km_init(command,parameter1) 
       function lyngby_ui_km_init

       Global: (from lyngby_km_global)
       This function controls the window for choosing the parameters
       used in the K-means clustering. In the window the following
       parameters can be set:

       - Type:  Whether the median or the mean of the cluster members
                is used to determine the next iterative cluster
       - Standardization: How to standardize (normalize) the
                individual objects (voxels). The objects can be
                standardize with their standard deviation (sigma) or
                with their range (the difference between the maximum
                and the minimum).
       - Clusters: Number of clusters. If the number of clusters are
                not known in advance you can use the iterative
                K-means clustering. See lyngby_ikm_main
       - Initial cluster centers: Determines how the cluster centers
                should be initialized.
       - Decay rate: (between 0 and 1) The weight between the cluster
                center in the previous iteration and the new estimate
                of the cluster center. (This will regularize the
                performance). A value of zero will only use new
       - Iterations (>0): Maximum number of iterations. If this is
                too small the optimization of the cluster centers
                might not be complete. 
       - Variable: Whether to cluster on the raw data vectors or the
                cross correlation between the paradigm and data
       - Components: Number of cross-correlation components to
                cluster from. This only applies when the variable
                (the metric) is cross-correlation. 

       When you have changed the parameters the 'Apply' button must
       be pressed before it will have an effect. 


 $Id: lyngby_ui_km_init.m,v 1.17 2002/09/27 12:51:28 fnielsen Exp $ 

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