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  2. Dictionary

    clus·ter
    [ˈkləstər]
    noun
    clusters (plural noun)
      • astronomy
        a group of stars or galaxies forming a relatively close association:
        "there are several clusters in Cassiopeia"
      • a natural subgroup of a population, used for statistical sampling or analysis:
        "ten clusters from all the primary health centers were selected"
      • a group of cases of a disease, especially an infectious disease or type of cancer, that occur close together in time or space:
        "clusters of the disease have been reported, leading to speculation about person-to-person transmission"
      • linguistics
        a group of consonants pronounced in immediate succession, as str in strong.
      • chemistry
        a group of atoms of the same element, typically a metal, bonded closely together in a molecule:
        "noble-metal clusters supported on an acidic carrier" · "a cluster compound"
    verb
    clusters (third person present)
    1. be or come into a cluster or close group; congregate:
      "the children clustered around her skirts" · "there were dozens of people clustered around me" · "the rich are likely to cluster together in suburbs"
      • statistics
        (of data points) have similar numerical values:
        "students tended to have scores clustering around 70 percent"
    Origin
    Old English clyster; probably related to clot.
    Translate cluster to
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  3. People also ask
    What is clustering in data analysis?Clustering is a technique used in data analysis to organize data into clusters based on similar features. The idea is that similar data are in each cluster, showing natural grouping within the data. You can choose to cluster based on different types of attributes like color, size, or type.
    What is clustering used for?Clustering has a myriad of uses in a variety of industries. Some common applications for clustering include the following: After clustering, each cluster is assigned a number called a cluster ID . Now, you can condense the entire feature set for an example into its cluster ID.
    What is a cluster based primarily on technology?Clusters are typically defined as collections or groups of items with similar or different characteristics. The group or collection of items constitutes a cluster. The following are three definitions of a cluster related primarily to technology. 1. Enterprise computing.
    What are examples of clustering?Examples of clusters can include genres of music, different groups of users, key segments of a market segmentation, types of network traffic on a server cluster, friend groups in a social network, or many other kinds of categories. The process of clustering can use just one feature of the data or it can use all of the features present in the data.
     
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  5. WebJul 18, 2022 · What are the Uses of Clustering? Clustering has a myriad of uses in a variety of industries. Some common applications for clustering include the following: market segmentation. social network...

  6. An Overview of Cluster Computing - GeeksforGeeks

    WebMar 31, 2021 · Cluster computing is a collection of tightly or loosely connected computers that work together so that they act as a single entity. The connected computers execute operations all together thus creating …

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  7. What is Clustering: An Introduction - Educative

  8. Cluster analysis - Wikipedia

  9. Data Cluster: Definition, Example, & Cluster Analysis

  10. Clusters - Institute For Strategy And Competitiveness - Harvard ...

  11. Clusters In Computer Organisation - GeeksforGeeks

  12. CLUSTER | English meaning - Cambridge Dictionary

  13. Clustering in Machine Learning - GeeksforGeeks

  14. Clusters, gaps, peaks & outliers (video) | Khan Academy

  15. What is Cluster Analysis: Methods and Examples | Airbyte

  16. CLUSTER definition and meaning | Collins English Dictionary

  17. What is a Kubernetes cluster? - Red Hat

  18. What is K Means Clustering? With an Example - Statistics By Jim

  19. K-Means Clustering Algorithm – What Is It and Why Does It Matter?

  20. Supervised vs. unsupervised learning: What's the difference? - IBM

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