[Y, c, Info] = lyngby_km_main(X, arg1, arg2, arg3, arg4, ...

lyngby_km_main - Main function for K-means clustering function [Y, c, Info] = lyngby_km_main(X, ... 'PropertyName', 'PropertyValue') Input: X Datamatrix, size: examples x variables. ie. if voxels are to be clustered the datamatrix should be (voxels x time). Property: Type [ {median} | mean ] Standardization [ {None} | Std | Range ] Determines the individual standardization (normalization) of the variables (the columns in the datamatrix. 'Std' will standardize with the standard deviation, 'Range' with the difference max-min Clusters [ {10} | Integer ] Number of clusters. Init [ {ReverseLog} | Linear | UpperLinear | Random ] Initial cluster centers determination. The variables are sorted according to max of xcorr or std of variables and the initial centers are chosen from this list. DecayRate Convergence control parameter, {0} < DecayRate <= 1. Determines how the clustering center converge. Iterations [ {20} | Integer ] Number of iterations. Variable [ {time} | xcorr ] Clustering with Cross correlation or time Paradigm Paradigm, the vector that is used in the cross-correlation with the datamatrix. This variable needs to be defined if the 'Variable' is 'xcorr' Components [ {40} | integer ] Number of cross-correlation components in the analysis. Not used if 'Variabel' is set to 'time'. Will max be set to the number of columns in X PositionWeight Smoothing of the clustering. Weight for the proximity part of the error function. Output: Y Cluster center matrix, size: Scans x 'Clusters' c Assignment vector for the all voxels Info Shows the convergence of the Y's (array of lenght 'Iterations'). lyngby_km_main performs K-means or K-median clustering. The number of clusters is specified with 'Clusters'. If 'Variable' is 'time' then the datamatrix X will be used (directly) as the input for the clustering algorithm. If 'Variable' is 'xcorr' then the cross-correlation between the datamatrix and the 'Paradigm' will be used as input. The individual variables (columns) in the datamatrix can be scaled according to 'Standardization': With 'Std' the columns are scaled to have equal standard deviation; with 'Range' the difference between minimum and maximum in each column is used to scale. Standardization should be used when the variables are measured with different units or the interesting features important for the discrimination lies in the variables with low magnitude. When the centers are found they are scaled back to the original space. 'Init' determines how the cluster centers are initialized. For all types of 'init' K specific objects (eg, voxels) are selected (K corresponding to the number of clusters): For 'random' the initial cluster centers are initialized by randomly picking K objects. For the other initialization methods the selection is deterministic from sorted objects. The sorting is either based on the standard deviation of the original data or the maximum of the cross-correlation function between the data and the paradigm. 'Linear' will select with linear space though the sorted list of objects, while 'reverselog' will select logarithmic through the list with the most cluster centers picked from the objects with the largest standard deviation or cross-correlation. 'UpperLinear' will select from the top of the list. Example: % K-means clustering of Fisher's iris data load iris.txt [Y,c,Info] = lyngby_km_main(iris,'type','mean','clusters',3); figure,plot(Info),title('Convergence'),xlabel('Iteration'); C=zeros(3,3);for n=1:150,C(ceil(n/50.1),c(n))=C(ceil(n/50.1),c(n))+1;end disp('Confusion matrix'), disp(C) See also LYNGBY, LYNGBY_KM_CENTERSIM, LYNGBY_KM_PLOT_DIST, LYNGBY_IKM_MAIN, LYNGBY_UI_KM_INIT, LYNGBY_XCORR. $Id: lyngby_km_main.m,v 1.28 2003/11/21 11:33:57 fnielsen Exp $

- lyngby_log export/lyngby/lyngby_log.m
- lyngby_mod export/lyngby/lyngby_mod.m
- lyngby_roi export/lyngby/lyngby_roi.m
- lyngby_set_uniqueexport/lyngby/lyngby_set_unique.m
- lyngby_xcorr export/lyngby/lyngby_xcorr.m

- lyngby_ikm_mainexport/lyngby/lyngby_ikm_main.m
- lyngby_ui_mkm_initexport/lyngby/lyngby_ui_mkm_init.m
- lyngby_uis_km export/lyngby/lyngby_uis_km.m
- lyngby_uis_mkm export/lyngby/lyngby_uis_mkm.m

Produced by mat2html on Wed Jul 29 15:43:40 2009

Cross-Directory links are: OFF