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FindClusters   (Built-in Mathematica Symbol)
FindClusters[{e_1, e_2, ...}] partitions the e i into clusters of similar elements. FindClusters[{e_1 -> v_1, e_2 -> v_2, ...}] returns the v_i corresponding to the e i in ...
Statistics`ClusterAnalysis`   (Mathematica Compatibility Information)
FindClusters and the distance and dissimilarity functions have been added to the built-in Mathematica kernel. SupDistance is replaced by ChessboardDistance. ...
Partitioning Data into Clusters   (Mathematica Tutorial)
Cluster analysis is an unsupervised learning technique used for classification of data. Data elements are partitioned into groups called clusters that represent proximate ...
Sequence Alignment & Comparison   (Mathematica Guide)
Mathematica includes state-of-the-art algorithms for sequence alignment and comparison, capable of handling strings and lists containing very large numbers of elements.
ColorQuantize   (Built-in Mathematica Symbol)
ColorQuantize[image, n] gives an approximation to image that uses only n distinct colors.
FindCurvePath   (Built-in Mathematica Symbol)
FindCurvePath[{{x_1, y_1}, {x_2, y_2}, ...}] gives an ordering of the {x_i, y_i} that corresponds to one or more smooth curves.
NearestFunction   (Built-in Mathematica Symbol)
NearestFunction[data] represents a function whose values give the elements closest to an element that is supplied.
Version 6.0 added a collection of carefully optimized functions to Mathematica's powerful arsenal of numerical handling capabilities.
Logic & Boolean Algebra   (Mathematica Guide)
Mathematica represents Boolean expressions in symbolic form, so they can not only be evaluated, but also be symbolically manipulated and transformed. Incorporating ...
MeanShift   (Built-in Mathematica Symbol)
MeanShift[list, d] replaces each element in list by the mean of the values of all elements that differ by less than d.
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