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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. pandas (software) - Wikipedia

    en.wikipedia.org/wiki/Pandas_(software)

    Pandas (styled as pandas) is a software library written for the Python programming language for data manipulation and analysis. In particular, it offers data structures and operations for manipulating numerical tables and time series .

  5. Grouped data - Wikipedia

    en.wikipedia.org/wiki/Grouped_data

    Another method of grouping the data is to use some qualitative characteristics instead of numerical intervals. For example, suppose in the above example, there are three types of students: 1) Below normal, if the response time is 5 to 14 seconds, 2) normal if it is between 15 and 24 seconds, and 3) above normal if it is 25 seconds or more, then the grouped data looks like:

  6. 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 ...

  7. Flajolet–Martin algorithm - Wikipedia

    en.wikipedia.org/wiki/Flajolet–Martin_algorithm

    A common solution is to combine both the mean and the median: Create hash functions and split them into distinct groups (each of size ). Within each group use the mean for aggregating together the l {\displaystyle l} results, and finally take the median of the k {\displaystyle k} group estimates as the final estimate.

  8. Universally unique identifier - Wikipedia

    en.wikipedia.org/wiki/Universally_unique_identifier

    A Universally Unique Identifier (UUID) is a 128-bit label used to uniquely identify objects in computer systems. The term Globally Unique Identifier (GUID) is also used, mostly in Microsoft systems. [1] [2] When generated according to the standard methods, UUIDs are, for practical purposes, unique.

  9. List of statistical tests - Wikipedia

    en.wikipedia.org/wiki/List_of_statistical_tests

    Statistical tests are used to test the fit between a hypothesis and the data. [1] [2] Choosing the right statistical test is not a trivial task. [1]The choice of the test depends on many properties of the research question.