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  2. Hierarchical clustering - Wikipedia

    en.wikipedia.org/wiki/Hierarchical_clustering

    The basic principle of divisive clustering was published as the DIANA (DIvisive ANAlysis clustering) algorithm. [20] Initially, all data is in the same cluster, and the largest cluster is split until every object is separate. Because there exist () ways of splitting each cluster, heuristics are needed. DIANA chooses the object with the maximum ...

  3. List of text mining methods - Wikipedia

    en.wikipedia.org/wiki/List_of_text_mining_methods

    Cluster Algorithm. Hierarchical Clustering. Agglomerative Clustering: Bottom-up approach. Each cluster is small and then aggregates together to form larger clusters. [3] Divisive Clustering: Top-down approach. Large clusters are split into smaller clusters. [3] Density-based Clustering: A structure is determined by the density of data points ...

  4. 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).

  5. 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.

  6. 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 ...

  7. ‘Divisive’ is the word of the year in the workplace, as ...

    www.aol.com/finance/brands-walmart-ford-drop-dei...

    Use of the word “divisive” grew by 33% this year, which Glassdoor said is a direct reflection of “election concerns, toxic workplaces, and shifts in company stances on DEI initiatives ...

  8. Hierarchical clustering of networks - Wikipedia

    en.wikipedia.org/wiki/Hierarchical_clustering_of...

    For this reason, their use in hierarchical clustering techniques is far from optimal. [1] Edge betweenness centrality has been used successfully as a weight in the Girvan–Newman algorithm. [1] This technique is similar to a divisive hierarchical clustering algorithm, except the weights are recalculated with each step.

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    This week, for example, you can get 40% off holiday kits that would be perfect stocking stuffers for the youngest beauty lover on your list, $100 off select Dyson hair tools and — perhaps our ...