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In computer science, linear search or sequential search is a method for finding an element within a list. It sequentially checks each element of the list until a match is found or the whole list has been searched. [1] A linear search runs in linear time in the worst case, and makes at most n comparisons, where n is the length of
The linear search problem for a general probability distribution is unsolved. [5] However, there exists a dynamic programming algorithm that produces a solution for any discrete distribution [6] and also an approximate solution, for any probability distribution, with any desired accuracy. [7]
In optimization, line search is a basic iterative approach to find a local minimum of an objective function:. It first finds a descent direction along which the objective function f {\displaystyle f} will be reduced, and then computes a step size that determines how far x {\displaystyle \mathbf {x} } should move along that direction.
Linear search algorithms check every record for the one associated with a target key in a linear fashion. [3] Binary, or half-interval, searches repeatedly target the center of the search structure and divide the search space in half. Comparison search algorithms improve on linear searching by successively eliminating records based on ...
Binary search Visualization of the binary search algorithm where 7 is the target value Class Search algorithm Data structure Array Worst-case performance O (log n) Best-case performance O (1) Average performance O (log n) Worst-case space complexity O (1) Optimal Yes In computer science, binary search, also known as half-interval search, logarithmic search, or binary chop, is a search ...
The analysis of the former and the latter algorithm shows that it takes at most log 2 n and n check steps, respectively, for a list of size n. In the depicted example list of size 33, searching for "Morin, Arthur" takes 5 and 28 steps with binary (shown in cyan) and linear (magenta) search, respectively.
The simplest, most general, and least efficient search structure is merely an unordered sequential list of all the items. Locating the desired item in such a list, by the linear search method, inevitably requires a number of operations proportional to the number n of items, in the worst case as well as in the average case. Useful search data ...
Wolfe's conditions are more complicated than Armijo's condition, and a gradient descent algorithm based on Armijo's condition has a better theoretical guarantee than one based on Wolfe conditions (see the sections on "Upper bound for learning rates" and "Theoretical guarantee" in the Backtracking line search article).