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The bust counts as a complete throw (i.e., 3 darts) even though only one dart is physically thrown. The remaining two darts in that turn are considered "used" but not scored because the score for the turn is zero. When a Player Wins the Leg on the First Dart of a Throw: If the winning dart is the first dart of a turn, only that dart is counted ...
The diagonal distance from the bull's eye to the oche, 9 ft 7 + 3 ⁄ 8 in (2.93 m), may also be used. In soft tipped darts, the perpendicular distance is 8 ft (2.44 m), as set by the American National Dart Association. This was the original distance first standardized by the British Darts Organisation for all darts.
A metric on a set X is a function (called the distance function or simply distance) d : X × X → R + (where R + is the set of non-negative real numbers). For all x, y, z in X, this function is required to satisfy the following conditions: d(x, y) ≥ 0 (non-negativity) d(x, y) = 0 if and only if x = y (identity of indiscernibles.
Data can be binary, ordinal, or continuous variables. It works by normalizing the differences between each pair of variables and then computing a weighted average of these differences. The distance was defined in 1971 by Gower [1] and it takes values between 0 and 1 with smaller values indicating higher similarity.
A measure for the dissimilarity of two shapes is given by Hausdorff distance up to isometry, denoted D H. Namely, let X and Y be two compact figures in a metric space M (usually a Euclidean space ); then D H ( X , Y ) is the infimum of d H ( I ( X ), Y ) among all isometries I of the metric space M to itself.
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.
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The total variation distance (or half the norm) arises as the optimal transportation cost, when the cost function is (,) =, that is, ‖ ‖ = (,) = {(): =, =} = [], where the expectation is taken with respect to the probability measure on the space where (,) lives, and the infimum is taken over all such with marginals and , respectively.