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  2. Production flow analysis - Wikipedia

    en.wikipedia.org/wiki/Production_flow_analysis

    Given a binary product-machines n-by-m matrix , rank order clustering [1] is an algorithm characterized by the following steps: . For each row i compute the number =; Order rows according to descending numbers previously computed

  3. 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 ...

  4. Cluster analysis - Wikipedia

    en.wikipedia.org/wiki/Cluster_analysis

    As listed above, clustering algorithms can be categorized based on their cluster model. The following overview will only list the most prominent examples of clustering algorithms, as there are possibly over 100 published clustering algorithms. Not all provide models for their clusters and can thus not easily be categorized.

  5. Microarray analysis techniques - Wikipedia

    en.wikipedia.org/wiki/Microarray_analysis_techniques

    K-means clustering is an algorithm for grouping genes or samples based on pattern into K groups. Grouping is done by minimizing the sum of the squares of distances between the data and the corresponding cluster centroid. Thus the purpose of K-means clustering is to classify data based on similar expression. [20]

  6. Cellular manufacturing - Wikipedia

    en.wikipedia.org/wiki/Cellular_manufacturing

    The algorithms for machine part grouping include Rank Order Clustering, Modified Rank Order Clustering, [18] and Similarity coefficients. There are also a number of mathematical models and algorithms to aid in planning a cellular manufacturing center, which take into account a variety of important variables such as, "multiple plant locations ...

  7. 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

  8. Potential contenders to replace Trudeau as Canadian prime ...

    www.aol.com/news/potential-contenders-replace...

    Canada's ruling Liberal Party is looking for a new leader to replace Prime Minister Justin Trudeau, who announced on Monday he intended to step down. Finance Minister Dominic LeBlanc said on ...

  9. Non-negative matrix factorization - Wikipedia

    en.wikipedia.org/wiki/Non-negative_matrix...

    A polynomial time algorithm for solving nonnegative rank factorization if V contains a monomial sub matrix of rank equal to its rank was given by Campbell and Poole in 1981. [40] Kalofolias and Gallopoulos (2012) [ 41 ] solved the symmetric counterpart of this problem, where V is symmetric and contains a diagonal principal sub matrix of rank r.