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  2. k-nearest neighbors algorithm - Wikipedia

    en.wikipedia.org/wiki/K-nearest_neighbors_algorithm

    An object is classified by a plurality vote of its neighbors, with the object being assigned to the class most common among its k nearest neighbors (k is a positive integer, typically small). If k = 1, then the object is simply assigned to the class of that single nearest neighbor. The k-NN algorithm can also be generalized for regression.

  3. Neighbourhood components analysis - Wikipedia

    en.wikipedia.org/wiki/Neighbourhood_components...

    Neighbourhood components analysis is a supervised learning method for classifying multivariate data into distinct classes according to a given distance metric over the data. . Functionally, it serves the same purposes as the K-nearest neighbors algorithm and makes direct use of a related concept termed stochastic nearest neighbo

  4. Nearest neighbour algorithm - Wikipedia

    en.wikipedia.org/wiki/Nearest_neighbour_algorithm

    Moreover, for each number of cities there is an assignment of distances between the cities for which the nearest neighbour heuristic produces the unique worst possible tour. (If the algorithm is applied on every vertex as the starting vertex, the best path found will be better than at least N/2-1 other tours, where N is the number of vertices.) [1]

  5. Kernel smoother - Wikipedia

    en.wikipedia.org/wiki/Kernel_smoother

    The k-nearest neighbor algorithm can be used for defining a k-nearest neighbor smoother as follows. For each point X 0 , take m nearest neighbors and estimate the value of Y ( X 0 ) by averaging the values of these neighbors.

  6. Distance matrix - Wikipedia

    en.wikipedia.org/wiki/Distance_matrix

    k = number of nearest neighbors selected; n = size of the training set; d = number of dimensions being used for the data; This classification focused model predicts the label of the target based on the distance matrix between the target and each of the training samples to determine the K-number of samples that are the closest/nearest to the target.

  7. Nearest neighbor search - Wikipedia

    en.wikipedia.org/wiki/Nearest_neighbor_search

    k-nearest neighbor search identifies the top k nearest neighbors to the query. This technique is commonly used in predictive analytics to estimate or classify a point based on the consensus of its neighbors. k-nearest neighbor graphs are graphs in which every point is connected to its k nearest neighbors.

  8. KNN - Wikipedia

    en.wikipedia.org/wiki/KNN

    k-nearest neighbors algorithm (k-NN), a method for classifying objects; Nearest neighbor graph (k-NNG), a graph connecting each point to its k nearest neighbors; Kabataan News Network, a Philippine television show made by teens; Khanna railway station, in Khanna, Punjab, India (by Indian Railways code)

  9. Nearest neighbor - Wikipedia

    en.wikipedia.org/wiki/Nearest_neighbor

    Nearest neighbor graph in geometry; Nearest neighbor function in probability theory; Nearest neighbor decoding in coding theory; The k-nearest neighbor algorithm in machine learning, an application of generalized forms of nearest neighbor search and interpolation; The nearest neighbour algorithm for approximately solving the travelling salesman ...