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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. 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).

  4. 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 ...

  5. Ward's method - Wikipedia

    en.wikipedia.org/wiki/Ward's_method

    Ward's minimum variance method can be defined and implemented recursively by a Lance–Williams algorithm. The Lance–Williams algorithms are an infinite family of agglomerative hierarchical clustering algorithms which are represented by a recursive formula for updating cluster distances at each step (each time a pair of clusters is merged).

  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. Today’s NYT ‘Strands’ Hints, Spangram and Answers for ...

    www.aol.com/today-nyt-strands-hints-spangram...

    An example spangram with corresponding theme words: PEAR, FRUIT, BANANA, APPLE, etc. Need a hint? Find non-theme words to get hints. For every 3 non-theme words you find, you earn a hint.

  8. 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 ...

  9. Top 5 nursing trends shaping health care in 2025 - AOL

    www.aol.com/top-5-nursing-trends-shaping...

    Vivian Health examines five trends that could redefine nurses' roles, enhance patient care, and alter the entire healthcare system in 2025 and beyond.