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  2. Fuzzy clustering - Wikipedia

    en.wikipedia.org/wiki/Fuzzy_clustering

    Fuzzy clustering (also referred to as soft clustering or soft k-means) is a form of clustering in which each data point can belong to more than one cluster.. Clustering or cluster analysis involves assigning data points to clusters such that items in the same cluster are as similar as possible, while items belonging to different clusters are as dissimilar as possible.

  3. Davies–Bouldin index - Wikipedia

    en.wikipedia.org/wiki/Davies–Bouldin_index

    The starting point for this new version of the validation index is the result of a given soft clustering algorithm (e.g. fuzzy c-means), shaped with the computed clustering partitions and membership values associating the elements with the clusters. In the soft domain, each element of the system belongs to every classes, given the membership ...

  4. Dunn index - Wikipedia

    en.wikipedia.org/wiki/Dunn_index

    The Dunn index (DI) (introduced by J. C. Dunn in 1974) is a metric for evaluating clustering algorithms. [1] [2] This is part of a group of validity indices including the Davies–Bouldin index or Silhouette index, in that it is an internal evaluation scheme, where the result is based on the clustered data itself.

  5. 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]

  6. Cluster analysis - Wikipedia

    en.wikipedia.org/wiki/Cluster_analysis

    Cluster analysis or clustering is the task of grouping a set of objects in such a way that objects in the same group (called a cluster) are more similar (in some specific sense defined by the analyst) to each other than to those in other groups (clusters).

  7. Model-based clustering - Wikipedia

    en.wikipedia.org/wiki/Model-based_clustering

    Several of these models correspond to well-known heuristic clustering methods. For example, k-means clustering is equivalent to estimation of the EII clustering model using the classification EM algorithm. [8] The Bayesian information criterion (BIC) can be used to choose the best clustering model as well as the number of clusters. It can also ...

  8. A top Fed official leans toward December rate cut but says it ...

    www.aol.com/top-fed-official-leans-toward...

    A top Federal Reserve official said Monday that he is leaning toward supporting an interest rate cut when the Fed meets in two weeks but that evidence of persistent inflation before then could ...

  9. List of cluster management software - Wikipedia

    en.wikipedia.org/wiki/List_of_cluster_management...

    ClusterVisor, [2] from Advanced Clustering Technologies [3] CycleCloud, from Cycle Computing acquired By Microsoft; Komodor, Enterprise Kubernetes Management Platform; Dell/EMC - Remote Cluster Manager (RCM) DxEnterprise, [4] from DH2i [5] Evidian SafeKit; HPE Performance Cluster Manager - HPCM, from Hewlett Packard Enterprise Company; IBM ...