Description: Performs hierarchical clustering of data using specified method and
seraches for optimal cutoff empoying VIF criterion suggested in "Okada Y. et al- Detection of Cluster Boundary in Microarray Data by Reference to MIPS Functional Catalogue Database (2001)".
Namely, it searches cutoff where groups are independent. The techinque uses an econometric approach of verifying that variables in
multiple regression are linearly independent: if all the diagonal
elements of inverse correlation matrix of data are less than VIF
- [my_clustering] - myself prepared by the Hierarchical clus
- [AddZerosDFT] - Zero Discrete Fourier Transform, high de
- [881] - An Efficient Algorithm for the cluster m
- [clustering] - Matlab Toolbox cluster analysis, is usef
- [dynimcCluster] - Matlab realize the dynamic clustering al
- [ConstSeg] - I placed design horizon surface.taking d
- [CLICKS] - clique code with sample data set. clique
- [edgedetect] - Own on the edge of the boundary detectio
- [KTree] - Construction of a hierarchical tree stru
- [C_PSO] - Particle cluster-like algorithm, for beg
File list (Check if you may need any files):
ClusterData.m
license.txt
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