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  2. Count–min sketch - Wikipedia

    en.wikipedia.org/wiki/Count–min_sketch

    The count–min sketch was invented in 2003 by Graham Cormode and S. Muthu Muthukrishnan [1] and described by them in a 2005 paper. [2] Count–min sketch is an alternative to count sketch and AMS sketch and can be considered an implementation of a counting Bloom filter (Fan et al., 1998 [3]) or multistage-filter. [1]

  3. pandas (software) - Wikipedia

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

    Pandas is built around data structures called Series and DataFrames. Data for these collections can be imported from various file formats such as comma-separated values, JSON, Parquet, SQL database tables or queries, and Microsoft Excel. [8] A Series is a 1-dimensional data structure built on top of NumPy's array.

  4. Counting sort - Wikipedia

    en.wikipedia.org/wiki/Counting_sort

    The initialization of the count array, and the second for loop which performs a prefix sum on the count array, each iterate at most k + 1 times and therefore take O(k) time. The other two for loops, and the initialization of the output array, each take O ( n ) time.

  5. Function composition (computer science) - Wikipedia

    en.wikipedia.org/wiki/Function_composition...

    In computer science, function composition is an act or mechanism to combine simple functions to build more complicated ones. Like the usual composition of functions in mathematics, the result of each function is passed as the argument of the next, and the result of the last one is the result of the whole.

  6. Count data - Wikipedia

    en.wikipedia.org/wiki/Count_data

    Graphical examination of count data may be aided by the use of data transformations chosen to have the property of stabilising the sample variance. In particular, the square root transformation might be used when data can be approximated by a Poisson distribution (although other transformation have modestly improved properties), while an inverse sine transformation is available when a binomial ...

  7. 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.

  8. Bloom filter - Wikipedia

    en.wikipedia.org/wiki/Bloom_filter

    If all are 1, then either the element is in the set, or the bits have by chance been set to 1 during the insertion of other elements, resulting in a false positive. In a simple Bloom filter, there is no way to distinguish between the two cases, but more advanced techniques can address this problem.

  9. Reference counting - Wikipedia

    en.wikipedia.org/wiki/Reference_counting

    As a collection algorithm, reference counting tracks, for each object, a count of the number of references to it held by other objects. If an object's reference count reaches zero, the object has become inaccessible, and can be destroyed. When an object is destroyed, any objects referenced by that object also have their reference counts decreased.