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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. Count-distinct problem - Wikipedia

    en.wikipedia.org/wiki/Count-distinct_problem

    In computer science, the count-distinct problem [1] (also known in applied mathematics as the cardinality estimation problem) is the problem of finding the number of distinct elements in a data stream with repeated elements. This is a well-known problem with numerous applications.

  4. Flajolet–Martin algorithm - Wikipedia

    en.wikipedia.org/wiki/Flajolet–Martin_algorithm

    The Flajolet–Martin algorithm is an algorithm for approximating the number of distinct elements in a stream with a single pass and space-consumption logarithmic in the maximal number of possible distinct elements in the stream (the count-distinct problem).

  5. 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).

  6. Table (database) - Wikipedia

    en.wikipedia.org/wiki/Table_(database)

    In a database, a table is a collection of related data organized in table format; consisting of columns and rows.. In relational databases, and flat file databases, a table is a set of data elements (values) using a model of vertical columns (identifiable by name) and horizontal rows, the cell being the unit where a row and column intersect. [1]

  7. Pivot table - Wikipedia

    en.wikipedia.org/wiki/Pivot_table

    Column labels are used to apply a filter to one or more columns that have to be shown in the pivot table. For instance if the "Salesperson" field is dragged to this area, then the table constructed will have values from the column "Sales Person", i.e., one will have a number of columns equal to the number of "Salesperson". There will also be ...

  8. HyperLogLog - Wikipedia

    en.wikipedia.org/wiki/HyperLogLog

    HyperLogLog is an algorithm for the count-distinct problem, approximating the number of distinct elements in a multiset. [1] Calculating the exact cardinality of the distinct elements of a multiset requires an amount of memory proportional to the cardinality, which is impractical for very large data sets. Probabilistic cardinality estimators ...

  9. Element distinctness problem - Wikipedia

    en.wikipedia.org/wiki/Element_distinctness_problem

    Elements that occur more than / times in a multiset of size may be found by a comparison-based algorithm, the Misra–Gries heavy hitters algorithm, in time (⁡). The element distinctness problem is a special case of this problem where k = n {\displaystyle k=n} .