clustering analysis
121Eigenvalue, eigenvector and eigenspace — In mathematics, given a linear transformation, an Audio|De eigenvector.ogg|eigenvector of that linear transformation is a nonzero vector which, when that transformation is applied to it, changes in length, but not direction. For each eigenvector… …
122GeoDA — is a free software package that conducts spatial data analysis, geovisualization, spatial autocorrelation and spatial modeling. The package was developed by the Spatial Analysis Laboratory of the University of Illinois at Urbana Champaign under… …
123Biological network inference — Many types of biological networks exist. Few such networks are known in anything approaching their complete structure, even in the simplest bacteria. Still less is known on the parameters governing the behavior of such networks over time, how the …
124Citation index — A citation index is a kind of bibliographic database, an index of citations between publications, allowing the user to easily establish which later documents cite which earlier documents. The first citation indices were legal citators such as… …
125Maximum spacing estimation — The maximum spacing method tries to find a distribution function such that the spacings, D(i), are all approximately of the same length. This is done by maximizing their geometric mean. In statistics, maximum spacing estimation (MSE or MSP), or… …
126OPTICS algorithm — OPTICS ( Ordering Points To Identify the Clustering Structure ) is an algorithm for finding density based clusters in spatial data. It was presented by Mihael Ankerst, Markus M. Breunig, Hans Peter Kriegel and Jörg Sander[1]. Its basic idea is… …
127Information bottleneck method — The information bottleneck method is a technique introduced by Tishby et al [1] for finding the best tradeoff between accuracy and complexity (compression) when summarizing (e.g. clustering) a random variable X, given a joint probability… …
128Scale-invariant feature transform — Feature detection Output of a typical corner detection algorithm …
