clustering method
11k-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… …
12Information 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… …
13Complete-linkage clustering — In cluster analysis, complete linkage or farthest neighbour is a method of calculating distances between clusters in agglomerative hierarchical clustering. In complete linkage,[1] the distance between two clusters is computed as the maximum… …
14Single-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 …
15Clique percolation method — The clique percolation method[1] is a popular approach for analyzing the overlapping community structure of networks. The term network community (also called a module, cluster or cohesive group) has no widely accepted unique definition and it is… …
16Sequence clustering — In bioinformatics, sequence clustering algorithms attempt to group sequences that are somehow related. The sequences can be either of genomic, transcriptomic (ESTs) or protein origin.For proteins, homologous sequences are typically grouped into… …
17Document clustering — (also referred to as Text clustering) is closely related to the concept of data clustering. Document clustering is a more specific technique for unsupervised document organization, automatic topic extraction and fast information retrieval or… …
18CURE 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… …
19Collaborative method — Collaborative methods are processes, behaviors and conversations that relate to collaboration between individuals.[1] These methods specifically aim to increase the success of teams as they engage in collaborative problem solving. Forms, rubrics …
20Unweighted Pair Group Method — with Arithmetic mean (kurz UPGMA) bezeichnet eine Bottom Up Clustering Methode. Sie wird oft in der Bioinformatik zur Rekonstruktion phylogenetischer Bäume angewendet. Im Gegensatz zu anderen Verfahren wie Neighbour Joining basiert UPGMA auf der… …
