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  2. Counting Bloom filter - Wikipedia

    en.wikipedia.org/wiki/Counting_Bloom_filter

    A counting Bloom filter is a probabilistic data structure that is used to test whether the number of occurrences of a given element in a sequence exceeds a given threshold. As a generalized form of the Bloom filter, false positive matches are possible, but false negatives are not – in other words, a query returns either "possibly bigger or equal than the threshold" or "definitely smaller ...

  3. Frequency (statistics) - Wikipedia

    en.wikipedia.org/wiki/Frequency_(statistics)

    A frequency distribution table is an arrangement of the values that one or more variables take in a sample. Each entry in the table contains the frequency or count of the occurrences of values within a particular group or interval, and in this way, the table summarizes the distribution of values in the sample.

  4. Flajolet–Martin algorithm - Wikipedia

    en.wikipedia.org/wiki/Flajolet–Martin_algorithm

    The algorithm was introduced by Philippe Flajolet and G. Nigel Martin in their 1984 article "Probabilistic Counting Algorithms for Data Base Applications". [1] Later it has been refined in "LogLog counting of large cardinalities" by Marianne Durand and Philippe Flajolet , [ 2 ] and " HyperLogLog : The analysis of a near-optimal cardinality ...

  5. Bag-of-words model - Wikipedia

    en.wikipedia.org/wiki/Bag-of-words_model

    3 Python implementation. 4 Hashing trick. 5 See also. 6 Notes. ... Each key is the word, and each value is the number of occurrences of that word in the given text ...

  6. Misra–Gries heavy hitters algorithm - Wikipedia

    en.wikipedia.org/wiki/Misra–Gries_heavy_hitters...

    In order to construct t, scan the values in b in arbitrary order, for specificity the following algorithm scans them in the order of increasing indices. Invariant P of the algorithm is that t is a k-reduced bag for the scanned values and d is the number of distinct values in t. Initially, no value has been scanned, t is the empty bag, and d is ...

  7. Count–min sketch - Wikipedia

    en.wikipedia.org/wiki/Count–min_sketch

    In computing, the count–min sketch (CM sketch) is a probabilistic data structure that serves as a frequency table of events in a stream of data.It uses hash functions to map events to frequencies, but unlike a hash table uses only sub-linear space, at the expense of overcounting some events due to collisions.

  8. Counting sort - Wikipedia

    en.wikipedia.org/wiki/Counting_sort

    For problem instances in which the maximum key value is significantly smaller than the number of items, counting sort can be highly space-efficient, as the only storage it uses other than its input and output arrays is the Count array which uses space O(k).

  9. Count-distinct problem - Wikipedia

    en.wikipedia.org/wiki/Count-distinct_problem

    Thus, the existence of duplicates does not affect the value of the extreme order statistics. There are other estimation techniques other than min/max sketches. The first paper on count-distinct estimation [7] describes the Flajolet–Martin algorithm, a bit pattern sketch. In this case, the elements are hashed into a bit vector and the sketch ...