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  2. Distance from a point to a line - Wikipedia

    en.wikipedia.org/wiki/Distance_from_a_point_to_a...

    Also, let Q = (x 1, y 1) be any point on this line and n the vector (a, b) starting at point Q. The vector n is perpendicular to the line, and the distance d from point P to the line is equal to the length of the orthogonal projection of on n. The length of this projection is given by:

  3. Array slicing - Wikipedia

    en.wikipedia.org/wiki/Array_slicing

    In computer programming, array slicing is an operation that extracts a subset of elements from an array and packages them as another array, possibly in a different dimension from the original. Common examples of array slicing are extracting a substring from a string of characters, the " ell " in "h ell o", extracting a row or column from a two ...

  4. Comparison of programming languages (array) - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_programming...

    This comparison of programming languages (array) compares the features of array data structures or matrix processing for various computer programming languages. Syntax [ edit ]

  5. Cosine similarity - Wikipedia

    en.wikipedia.org/wiki/Cosine_similarity

    The most noteworthy property of cosine similarity is that it reflects a relative, rather than absolute, comparison of the individual vector dimensions. For any positive constant and vector , the vectors and are maximally similar. The measure is thus most appropriate for data where frequency is more important than absolute values; notably, term ...

  6. Euclidean distance - Wikipedia

    en.wikipedia.org/wiki/Euclidean_distance

    By Dvoretzky's theorem, every finite-dimensional normed vector space has a high-dimensional subspace on which the norm is approximately Euclidean; the Euclidean norm is the only norm with this property. [24] It can be extended to infinite-dimensional vector spaces as the L 2 norm or L 2 distance. [25]

  7. Euclidean vector - Wikipedia

    en.wikipedia.org/wiki/Euclidean_vector

    A vector of arbitrary length can be divided by its length to create a unit vector. [14] This is known as normalizing a vector. A unit vector is often indicated with a hat as in â. To normalize a vector a = (a 1, a 2, a 3), scale the vector by the reciprocal of its length ‖a‖. That is:

  8. 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 ...

  9. Norm (mathematics) - Wikipedia

    en.wikipedia.org/wiki/Norm_(mathematics)

    In mathematics, a norm is a function from a real or complex vector space to the non-negative real numbers that behaves in certain ways like the distance from the origin: it commutes with scaling, obeys a form of the triangle inequality, and is zero only at the origin.