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Search algorithm. In computer science, a search algorithm is an algorithm designed to solve a search problem. Search algorithms work to retrieve information stored within particular data structure, or calculated in the search space of a problem domain, with either discrete or continuous values . Although search engines use search algorithms ...
Breadth-first search ( BFS) is an algorithm for searching a tree data structure for a node that satisfies a given property. It starts at the tree root and explores all nodes at the present depth prior to moving on to the nodes at the next depth level. Extra memory, usually a queue, is needed to keep track of the child nodes that were ...
Nassi–Shneiderman diagram. A Nassi–Shneiderman diagram (NSD) in computer programming is a graphical design representation for structured programming. [1] This type of diagram was developed in 1972 by Isaac Nassi and Ben Shneiderman who were both graduate students at Stony Brook University. [2]
Naranjo algorithm. The Naranjo algorithm, Naranjo Scale, or Naranjo Nomogram is a questionnaire designed by Naranjo et al. for determining the likelihood of whether an adverse drug reaction (ADR) is actually due to the drug rather than the result of other factors. Probability is assigned via a score termed definite, probable, possible or doubtful.
Tabu search is a metaheuristic algorithm that can be used for solving combinatorial optimization problems (problems where an optimal ordering and selection of options is desired). Current applications of TS span the areas of resource planning, telecommunications, VLSI design, financial analysis, scheduling, space planning, energy distribution ...
k. -nearest neighbors algorithm. In statistics, the k-nearest neighbors algorithm ( k-NN) is a non-parametric supervised learning method first developed by Evelyn Fix and Joseph Hodges in 1951, [1] and later expanded by Thomas Cover. [2] It is used for classification and regression. In both cases, the input consists of the k closest training ...
A randomized algorithm is an algorithm that employs a degree of randomness as part of its logic or procedure. The algorithm typically uses uniformly random bits as an auxiliary input to guide its behavior, in the hope of achieving good performance in the "average case" over all possible choices of random determined by the random bits; thus either the running time, or the output (or both) are ...
In computer science, the analysis of algorithms is the process of finding the computational complexity of algorithms —the amount of time, storage, or other resources needed to execute them. Usually, this involves determining a function that relates the size of an algorithm's input to the number of steps it takes (its time complexity) or the ...