Such insight can be useful in improving some algorithms on graphs such as spectral clustering. Examples for such clustering algorithms are CLIQUE and SUBCLU. This proximity is used as input of average linkage hierarchical clustering. Correlation clustering looks for natural clustering of data by similarity. DBSCAN is also used as part of subspace clustering algorithms like PreDeCon and SUBCLU. Complete-linkage clustering is one of several methods of agglomerative hierarchical clustering. In statistics, single-linkage clustering is one of several methods of hierarchical clustering. The results of hierarchical clustering are usually presented in a dendrogram. For example, a 2-layer feedforward network for data clustering and classification. Remote sensing has contributed extensively in morphometric and clustering analysis. Conductance also helps measure the quality of a Spectral clustering. This provides a theoretical foundation for using NMF for data clustering. This is an implementation of an unsupervised Naive Bayes model for document clustering. Given is gray scale image that has undergone fuzzy clustering in Matlab. I molecules triggers receptor clustering and redistribution.