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The distance (or perpendicular distance) from a point to a line is the shortest distance from a fixed point to any point on a fixed infinite line in Euclidean geometry. It is the length of the line segment which joins the point to the line and is perpendicular to the line. The formula for calculating it can be derived and expressed in several ways.
In mathematics, the Euclidean distance between two points in Euclidean space is the length of the line segment between them. It can be calculated from the Cartesian coordinates of the points using the Pythagorean theorem , and therefore is occasionally called the Pythagorean distance .
The formula for the closest point to the origin may be expressed more succinctly using notation from linear algebra. The expression a x + b y + c z {\displaystyle ax+by+cz} in the definition of a plane is a dot product ( a , b , c ) ⋅ ( x , y , z ) {\displaystyle (a,b,c)\cdot (x,y,z)} , and the expression a 2 + b 2 + c 2 {\displaystyle a^{2 ...
The Canberra distance is a numerical measure of the distance between pairs of points in a vector space, introduced in 1966 [1] and refined in 1967 [2] by Godfrey N. Lance and William T. Williams. It is a weighted version of L ₁ (Manhattan) distance . [ 3 ]
This article uses the convention that vectors are denoted in a bold font (e.g. a 1), and scalars are written in normal font (e.g. a 1). The dot product of vectors a and b is written as a ⋅ b {\displaystyle \mathbf {a} \cdot \mathbf {b} } , the norm of a is written ‖ a ‖, the angle between a and b is denoted θ .
In statistics and in probability theory, distance correlation or distance covariance is a measure of dependence between two paired random vectors of arbitrary, not necessarily equal, dimension. The population distance correlation coefficient is zero if and only if the random vectors are independent .
The distance between the points and is , the distance between the points and is = and the distance between the points and is = +. The value A {\displaystyle A} is positive or negative depending on which of the points P 1 {\displaystyle P_{1}} and P 2 {\displaystyle P_{2}} that is furthest away from the point F 1 {\displaystyle F_{1}} .
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.