- clustering algorithm
- алгоритм кластеризации
The New English-Russian Dictionary of Radio-electronics. F.V Lisovsky . 2005.
clustering algorithm
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CURE data clustering algorithm — CURE (Clustering Using REpresentatives) is an efficient data clustering algorithm for large databases that is more robust to outliers and identifies clusters having non spherical shapes and wide variances in size. Contents 1 Drawbacks of… … Wikipedia
Canopy clustering algorithm — The canopy clustering algorithm is an unsupervised clustering algorithm related to the K means algorithm.It is intended to speed up clustering operations on large data sets, where using another algorithm directly may be impractical because of the … Wikipedia
Clustering high-dimensional data — is the cluster analysis of data with anywhere from a few dozen to many thousands of dimensions. Such high dimensional data spaces are often encountered in areas such as medicine, where DNA microarray technology can produce a large number of… … Wikipedia
Clustering — can refer to the following: In demographics: Clustering (demographics), the gathering of various populations based on factors such as ethnicity, economics or religion. In graph theory: The formation of clusters of linked nodes in a network,… … Wikipedia
Consensus clustering — Clustering is the assignment of objects into groups (called clusters) so that objects from the same cluster are more similar to each other than objects from different clusters. Often similarity is assessed according to a distance measure.… … Wikipedia
Clustering — Unter Clusteranalyse (der Begriff Ballungsanalyse wird selten verwendet) versteht man strukturentdeckende, multivariate Analyseverfahren zur Ermittlung von Gruppen (Clustern) von Objekten, deren Eigenschaften oder Eigenschaftsausprägungen… … Deutsch Wikipedia
Clustering-Verfahren — Unter Clusteranalyse (der Begriff Ballungsanalyse wird selten verwendet) versteht man strukturentdeckende, multivariate Analyseverfahren zur Ermittlung von Gruppen (Clustern) von Objekten, deren Eigenschaften oder Eigenschaftsausprägungen… … Deutsch Wikipedia
k-means clustering — In statistics and data mining, k means clustering is a method of cluster analysis which aims to partition n observations into k clusters in which each observation belongs to the cluster with the nearest mean. This results into a partitioning of… … Wikipedia
Nearest-neighbor chain algorithm — In the theory of cluster analysis, the nearest neighbor chain algorithm is a method that can be used to perform several types of agglomerative hierarchical clustering, using an amount of memory that is linear in the number of points to be… … Wikipedia
K-means algorithm — The k means algorithm is an algorithm to cluster n objects based on attributes into k partitions, k < n. It is similar to the expectation maximization algorithm for mixtures of Gaussians in that they both attempt to find the centers of natural… … Wikipedia
Single-linkage clustering — In cluster analysis, single linkage, nearest neighbour or shortest distance is a method of calculating distances between clusters in hierarchical clustering. In single linkage, the distance between two clusters is computed as the distance between … Wikipedia
