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  2. Similarity learning - Wikipedia

    en.wikipedia.org/wiki/Similarity_learning

    Similarity learning is closely related to distance metric learning.Metric learning is the task of learning a distance function over objects. A metric or distance function has to obey four axioms: non-negativity, identity of indiscernibles, symmetry and subadditivity (or the triangle inequality).

  3. Similarity measure - Wikipedia

    en.wikipedia.org/wiki/Similarity_measure

    In statistics and related fields, a similarity measure or similarity function or similarity metric is a real-valued function that quantifies the similarity between two objects. Although no single definition of a similarity exists, usually such measures are in some sense the inverse of distance metrics : they take on large values for similar ...

  4. Jaro–Winkler distance - Wikipedia

    en.wikipedia.org/wiki/Jaro–Winkler_distance

    The higher the Jaro–Winkler distance for two strings is, the less similar the strings are. The score is normalized such that 0 means an exact match and 1 means there is no similarity. The original paper actually defined the metric in terms of similarity, so the distance is defined as the inversion of that value (distance = 1 − similarity).

  5. Gower's distance - Wikipedia

    en.wikipedia.org/wiki/Gower's_distance

    In statistics, Gower's distance between two mixed-type objects is a similarity measure that can handle different types of data within the same dataset and is particularly useful in cluster analysis or other multivariate statistical techniques. Data can be binary, ordinal, or continuous variables.

  6. MinHash - Wikipedia

    en.wikipedia.org/wiki/MinHash

    The simplest version of the minhash scheme uses k different hash functions, where k is a fixed integer parameter, and represents each set S by the k values of h min (S) for these k functions. To estimate J ( A , B ) using this version of the scheme, let y be the number of hash functions for which h min ( A ) = h min ( B ) , and use y / k as the ...

  7. Hamming distance - Wikipedia

    en.wikipedia.org/wiki/Hamming_distance

    For a fixed length n, the Hamming distance is a metric on the set of the words of length n (also known as a Hamming space), as it fulfills the conditions of non-negativity, symmetry, the Hamming distance of two words is 0 if and only if the two words are identical, and it satisfies the triangle inequality as well: [2] Indeed, if we fix three words a, b and c, then whenever there is a ...

  8. Python syntax and semantics - Wikipedia

    en.wikipedia.org/wiki/Python_syntax_and_semantics

    A snippet of Python code with keywords highlighted in bold yellow font. The syntax of the Python programming language is the set of rules that defines how a Python program will be written and interpreted (by both the runtime system and by human readers). The Python language has many similarities to Perl, C, and Java. However, there are some ...

  9. Gestalt pattern matching - Wikipedia

    en.wikipedia.org/wiki/Gestalt_Pattern_Matching

    The similarity of two strings and is determined by this formula: twice the number of matching characters divided by the total number of characters of both strings. The matching characters are defined as some longest common substring [3] plus recursively the number of matching characters in the non-matching regions on both sides of the longest common substring: [2] [4]