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Qué (quién) es nearest$514106$ - definición

SIMPLE METHOD OF MULTIVARIATE INTERPOLATION IN ONE OR MORE DIMENSIONS

Proximal interpolation; Nearest Neighbor Interpolation; Nearest neighbour interpolation; Point sampling; Nearest neighbor interpolation; Nearest-neighbour interpolation; Nearest neighbor interpolation algorithm

K-nearest neighbors algorithm

CLASSIFICATION ALGORITHM

Nearest neighbor (pattern recognition); Nearest Neighbor (Pattern Recognition); K-Nearest Neighbor algorithm; K-nearest-neighbor estimator; K-nearest neighbour algorithm; K-nearest neighbor; K-nearest neighbour; K-NN; Ibk algorithm; K nearest neighbors; K-nearest neighbours algorithm; K-nearest neighbors; K-nearest neighbors problem; K-nearest neighbor problem; K-Nearest Neighbours; K-nearest-neighbor; K-nearest-neighbor algorithm; Nearest neighbour classifiers; K-nearest neighbor algorithm; K-nearest neighbors classification; K-Nearest Neighbors; K-Nearest Neighbour; Nearest neighbors classifier; K-NN regression; K-NN algorithm; KNN lookup; KNN algorithm; Nearest neighbor decision rule

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, and later expanded by Thomas Cover. It is used for classification and regression.

https://en.wikipedia.org/wiki/K-nearest_neighbors_algorithm

Nearest neighbor graph

TYPE OF DIRECTED GRAPH

Nearest neighbour graph; Nearest-neighbour graph; Farthest neighbor graph; Furthest neighbor graph; Nearest-neighbor graph; Farthest-neighbor graph; Furthest-neighbor graph

The nearest neighbor graph (NNG) is a directed graph defined for a set of points in a metric space, such as the Euclidean distance in the plane. The NNG has a vertex for each point, and a directed edge from p to q whenever q is a nearest neighbor of p, a point whose distance from p is minimum among all the given points other than p itself.

https://en.wikipedia.org/wiki/Nearest_neighbor_graph

Nearest neighbor search

(AS A FORM OF PROXIMITY SEARCH (METRIC SPACE)) OPTIMIZATION PROBLEM OF FINDING THE POINT IN A GIVEN SET THAT IS CLOSEST (OR MOST SIMILAR) TO A GIVEN POINT

Nearest neighbor problem; Proximity search (metric space); Nearest neighbour search; Closest point search; Nearest neighbour problem; Closest point query; Nearest neighbor query; Nearest neighbour query; Post-office problem; Post office problem; Nearest neighbor method; Post-office search algorithm; Approximate nearest-neighbor search algorithm; Approximation algorithms for nearest-neighbor search; Nearest neighbor distance ratio; Approximate nearest neighbor search algorithms; Applications of nearest neighbor search

Nearest neighbor search (NNS), as a form of proximity search, is the optimization problem of finding the point in a given set that is closest (or most similar) to a given point. Closeness is typically expressed in terms of a dissimilarity function: the less similar the objects, the larger the function values.

https://en.wikipedia.org/wiki/Nearest_neighbor_search

Wikipedia

Nearest-neighbor interpolation

Nearest-neighbor interpolation (also known as proximal interpolation or, in some contexts, point sampling) is a simple method of multivariate interpolation in one or more dimensions.

Interpolation is the problem of approximating the value of a function for a non-given point in some space when given the value of that function in points around (neighboring) that point. The nearest neighbor algorithm selects the value of the nearest point and does not consider the values of neighboring points at all, yielding a piecewise-constant interpolant. The algorithm is very simple to implement and is commonly used (usually along with mipmapping) in real-time 3D rendering to select color values for a textured surface.

https://en.wikipedia.org/wiki/Nearest-neighbor interpolation