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  2. Distance between two parallel lines - Wikipedia

    en.wikipedia.org/wiki/Distance_between_two...

    the distance between the two lines is the distance between the two intersection points of these lines with the perpendicular line = /. This distance can be found by first solving the linear systems {= + = /, and {= + = /, to get the coordinates of the intersection points. The solutions to the linear systems are the points

  3. Minkowski distance - Wikipedia

    en.wikipedia.org/wiki/Minkowski_distance

    The Minkowski distance can also be viewed as a multiple of the power mean of the component-wise differences between and . The following figure shows unit circles (the level set of the distance function where all points are at the unit distance from the center) with various values of p {\displaystyle p} :

  4. Hamming distance - Wikipedia

    en.wikipedia.org/wiki/Hamming_distance

    In information theory, the Hamming distance between two strings or vectors of equal length is the number of positions at which the corresponding symbols are different. In other words, it measures the minimum number of substitutions required to change one string into the other, or equivalently, the minimum number of errors that could have transformed one string into the other.

  5. Analytic geometry - Wikipedia

    en.wikipedia.org/wiki/Analytic_geometry

    For example, using Cartesian coordinates on the plane, the distance between two points (x 1, y 1) and (x 2, y 2) is defined by the formula = + (), which can be viewed as a version of the Pythagorean theorem.

  6. Euclidean distance - Wikipedia

    en.wikipedia.org/wiki/Euclidean_distance

    That is (unlike road distance with one-way streets) the distance between two points does not depend on which of the two points is the start and which is the destination. [11] It is positive, meaning that the distance between every two distinct points is a positive number, while the distance from any point to itself is zero. [11]

  7. Euclidean vector - Wikipedia

    en.wikipedia.org/wiki/Euclidean_vector

    If the dot product of two vectors is defined—a scalar-valued product of two vectors—then it is also possible to define a length; the dot product gives a convenient algebraic characterization of both angle (a function of the dot product between any two non-zero vectors) and length (the square root of the dot product of a vector by itself).

  8. Distance geometry - Wikipedia

    en.wikipedia.org/wiki/Distance_geometry

    Distance geometry is the branch of mathematics concerned with characterizing and studying sets of points based only on given values of the distances between pairs of points. [ 1 ] [ 2 ] [ 3 ] More abstractly, it is the study of semimetric spaces and the isometric transformations between them.

  9. Similarity measure - Wikipedia

    en.wikipedia.org/wiki/Similarity_measure

    For each type of object there are various similarity measurement formulas. [2] Similarity between two data points. Image shows the path of calculation when using the Euclidean distance formula. There are many various options available when it comes to finding similarity between two data points, some of which are a combination of other ...