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

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

    The average silhouette of the data is another useful criterion for assessing the natural number of clusters. The silhouette of a data instance is a measure of how closely it is matched to data within its cluster and how loosely it is matched to data of the neighboring cluster, i.e., the cluster whose average distance from the datum is lowest. [8]

  3. Worksheet - Wikipedia

    en.wikipedia.org/wiki/Worksheet

    In spreadsheet programs like the open source LibreOffice Calc or Microsoft's Excel, a single document is known as a 'workbook' and may have by default three arrays or 'worksheets'. One advantage of such programs is that they can contain formulae so that if one cell value is changed, the entire document is automatically updated, based on those ...

  4. Cluster diagram - Wikipedia

    en.wikipedia.org/wiki/Cluster_diagram

    A cluster in general is a group or bunch of several discrete items that are close to each other. The cluster diagram figures a cluster, such as a network diagram figures a network, a flow diagram a process or movement of objects, and a tree diagram an abstract tree. But all these diagrams can be considered interconnected: A network diagram can ...

  5. Bar chart - Wikipedia

    en.wikipedia.org/wiki/Bar_chart

    Example of a grouped (clustered) bar chart, one with horizontal bars. A bar chart or bar graph is a chart or graph that presents categorical data with rectangular bars with heights or lengths proportional to the values that they represent.

  6. Model-based clustering - Wikipedia

    en.wikipedia.org/wiki/Model-based_clustering

    The poLCA package [38] clusters categorical data using the latent class model. The clustMD package [25] clusters mixed data, including continuous, binary, ordinal and nominal variables. The flexmix package [39] does model-based clustering for a range of component distributions. The mixtools package [40] can cluster different

  7. Clustering high-dimensional data - Wikipedia

    en.wikipedia.org/wiki/Clustering_high...

    Clustering high-dimensional data is the cluster analysis of data with anywhere from a few dozen to many thousands of dimensions.Such high-dimensional spaces of data are often encountered in areas such as medicine, where DNA microarray technology can produce many measurements at once, and the clustering of text documents, where, if a word-frequency vector is used, the number of dimensions ...

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

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

    Move over, Wordle and Connections—there's a new NYT word game in town! The New York Times' recent game, "Strands," is becoming more and more popular as another daily activity fans can find on ...

  9. Automatic clustering algorithms - Wikipedia

    en.wikipedia.org/wiki/Automatic_Clustering...

    Therefore, new algorithms based on BIRCH have been developed in which there is no need to provide the cluster count from the beginning, but that preserves the quality and speed of the clusters. The main modification is to remove the final step of BIRCH, where the user had to input the cluster count, and to improve the rest of the algorithm ...

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