Additive clustering and qualitative factor analysis methods for similarity matrices

CUR Decompositions, Similarity Matrices, and Subspace Clustering

A general framework for solving the subspace clustering problem using the CUR decomposition is presented. The CUR decomposition provides a natural way to construct similarity matrices for data that come from a union of unknown subspaces U = M ⋃ i=1 Si. The similarity matrices thus constructed give the exact clustering in the noise-free case. A simple adaptation of the technique also allows clus...

Additive spectral method for fuzzy cluster analysis of similarity data including community structure and affinity matrices

An additive spectral method for fuzzy clustering is proposed. The method operates on a clustering model which is an extension of the spectral decomposition of a square matrix. The computation proceeds by extracting clusters one by one which makes the spectral approach quite natural. The iterative extraction of clusters, also, allows us to draw several stopping rules to the procedure. This appli...

Two modified Jacobi methods for M-matrices

Using Clustering and Factor Analysis in Cross Section Analysis Based on Economic-Environment Factors

Homogeneity of groups in studies those use cross section and multi-level data is important. Most studies in economics especially panel data analysis need some kinds of homogeneity to ensure validity of results. This paper represents the methods known as clustering and homogenization of groups in cross section studies based on enviro-economics components. For this, a sample of 92 countries which...

Similarity of position frequency matrices for transcription factor binding sites

MOTIVATION Transcription-factor binding sites (TFBS) in promoter sequences of higher eukaryotes are commonly modeled using position frequency matrices (PFM). The ability to compare PFMs representing binding sites is especially important for de novo sequence motif discovery, where it is desirable to compare putative matrices to one another and to known matrices. RESULTS We describe a PFM simil...