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  2. k-nearest neighbors algorithm - Wikipedia

    en.wikipedia.org/wiki/K-nearest_neighbors_algorithm

    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. In k-NN regression, also known as nearest neighbor smoothing, the output is the property value for the object. This value is the average of the values of k nearest neighbors.

  3. Nearest neighbour algorithm - Wikipedia

    en.wikipedia.org/wiki/Nearest_neighbour_algorithm

    If all the vertices in the domain are visited, then terminate. Else, go to step 3. The sequence of the visited vertices is the output of the algorithm. The nearest neighbour algorithm is easy to implement and executes quickly, but it can sometimes miss shorter routes which are easily noticed with human insight, due to its "greedy" nature.

  4. 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.

  5. Nearest neighbour distribution - Wikipedia

    en.wikipedia.org/wiki/Nearest_neighbour_distribution

    In probability and statistics, a nearest neighbor function, nearest neighbor distance distribution, [1] nearest-neighbor distribution function [2] or nearest neighbor distribution [3] is a mathematical function that is defined in relation to mathematical objects known as point processes, which are often used as mathematical models of physical phenomena representable as randomly positioned ...

  6. 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 ...

  7. iDistance - Wikipedia

    en.wikipedia.org/wiki/IDistance

    In pattern recognition, the iDistance is an indexing and query processing technique for k-nearest neighbor queries on point data in multi-dimensional metric spaces.The kNN query is one of the hardest problems on multi-dimensional data, especially when the dimensionality of the data is high.

  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 graph - Wikipedia

    en.wikipedia.org/wiki/Nearest_neighbor_graph

    For situations in which it is necessary to make the nearest neighbor for each object unique, the set P may be indexed and in the case of a tie the object with, e.g., the largest index may be taken as the nearest neighbor. [2] The k-nearest neighbors graph (k-NNG) is a graph in which two vertices p and q are connected by an edge, if the distance ...