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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. Cluster analysis - Wikipedia

    en.wikipedia.org/wiki/Cluster_analysis

    Hard clustering: each object belongs to a cluster or not; Soft clustering (also: fuzzy clustering): each object belongs to each cluster to a certain degree (for example, a likelihood of belonging to the cluster) There are also finer distinctions possible, for example: Strict partitioning clustering: each object belongs to exactly one cluster

  4. 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 ...

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

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

    When clustering text databases with the cover coefficient on a document collection defined by a document by term D matrix (of size m×n, where m is the number of documents and n is the number of terms), the number of clusters can roughly be estimated by the formula where t is the number of non-zero entries in D. Note that in D each row and each ...

  6. Document clustering - Wikipedia

    en.wikipedia.org/wiki/Document_clustering

    Hard clustering computes a hard assignment – each document is a member of exactly one cluster. The assignment of soft clustering algorithms is soft – a document's assignment is a distribution over all clusters. In a soft assignment, a document has fractional membership in several clusters. [1]: 499 Dimensionality reduction methods can be ...

  7. Allworth Advice: Hard vs. soft inquiries - AOL

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  8. k-medoids - Wikipedia

    en.wikipedia.org/wiki/K-medoids

    k-medoids is a classical partitioning technique of clustering that splits the data set of n objects into k clusters, where the number k of clusters assumed known a priori (which implies that the programmer must specify k before the execution of a k-medoids algorithm).

  9. Bahamas 'firmly rejected' Trump proposal to deport immigrants ...

    www.aol.com/bahamas-firmly-rejected-trump...

    The Bahamas has “firmly rejected” President-election Donald Trump's proposal to fly deported immigrants out of the U.S. and into the small island nation about 100 miles southeast of Florida ...