enow.com Web Search

Search results

  1. Results from the WOW.Com Content Network
  2. Ward's method - Wikipedia

    en.wikipedia.org/wiki/Ward's_method

    In statistics, Ward's method is a criterion applied in hierarchical cluster analysis. Ward's minimum variance method is a special case of the objective function approach originally presented by Joe H. Ward, Jr. [ 1 ] Ward suggested a general agglomerative hierarchical clustering procedure, where the criterion for choosing the pair of clusters ...

  3. Hierarchical clustering - Wikipedia

    en.wikipedia.org/wiki/Hierarchical_clustering

    The standard algorithm for hierarchical agglomerative clustering (HAC) has a time complexity of () and requires () memory, which makes it too slow for even medium data sets. . However, for some special cases, optimal efficient agglomerative methods (of complexity ()) are known: SLINK [2] for single-linkage and CLINK [3] for complete-linkage clusteri

  4. Cluster analysis - Wikipedia

    en.wikipedia.org/wiki/Cluster_analysis

    Markov chain Monte Carlo methods Clustering is often utilized to locate and characterize extrema in the target distribution. Anomaly detection Anomalies/outliers are typically – be it explicitly or implicitly – defined with respect to clustering structure in data. Natural language processing Clustering can be used to resolve lexical ...

  5. Group concept mapping - Wikipedia

    en.wikipedia.org/wiki/Group_concept_mapping

    The data is then analyzed using The Concept System software, which creates a series of interrelated maps using multidimensional scaling (MDS) of the sort data, hierarchical clustering of the MDS coordinates applying Ward's method, and the computation of average ratings for each statement and cluster of statements. [17]

  6. Nearest-neighbor chain algorithm - Wikipedia

    en.wikipedia.org/wiki/Nearest-neighbor_chain...

    In the theory of cluster analysis, the nearest-neighbor chain algorithm is an algorithm that can speed up several methods for agglomerative hierarchical clustering.These are methods that take a collection of points as input, and create a hierarchy of clusters of points by repeatedly merging pairs of smaller clusters to form larger clusters.

  7. Determining the number of clusters in a data set - Wikipedia

    en.wikipedia.org/wiki/Determining_the_number_of...

    The average silhouette of the data is another useful criterion for assessing the natural number of clusters. The silhouette of a data instance is a measure of how closely it is matched to data within its cluster and how loosely it is matched to data of the neighboring cluster, i.e., the cluster whose average distance from the datum is lowest. [8]

  8. Eat macadamia nuts, prioritize sleep, exercise 1 hour per day ...

    www.aol.com/lifestyle/bryan-johnsons-dont-die...

    As Johnson noted in his speech, building strong ties with others helps ward off mental illness like depression and anxiety, and may even increase your lifespan. Whether that’s a hike with ...

  9. Category:Cluster analysis algorithms - Wikipedia

    en.wikipedia.org/wiki/Category:Cluster_analysis...

    Data stream clustering; DBSCAN; E. Expectation–maximization algorithm; F. ... Ward's method; WPGMA This page was last edited on 6 August 2017, at 17:28 (UTC). ...