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  2. Nearest neighbor search - Wikipedia

    en.wikipedia.org/wiki/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.

  3. k-nearest neighbors algorithm - Wikipedia

    en.wikipedia.org/wiki/K-nearest_neighbors_algorithm

    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. If k = 1, then the output is simply assigned to the value of that single nearest neighbor, also known as nearest neighbor interpolation.

  4. 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 ...

  5. Isomap - Wikipedia

    en.wikipedia.org/wiki/Isomap

    Isomap is used for computing a quasi-isometric, low-dimensional embedding of a set of high-dimensional data points. The algorithm provides a simple method for estimating the intrinsic geometry of a data manifold based on a rough estimate of each data point’s neighbors on the manifold. Isomap is highly efficient and generally applicable to a ...

  6. Hierarchical navigable small world - Wikipedia

    en.wikipedia.org/wiki/Hierarchical_navigable...

    The Hierarchical navigable small world (HNSW) algorithm is a graph-based approximate nearest neighbor search technique used in many vector databases. [1] [2] Nearest neighbor search without an index involves computing the distance from the query to each point in the database, which for large datasets is computationally prohibitive.

  7. Nearest neighbour algorithm - Wikipedia

    en.wikipedia.org/wiki/Nearest_neighbour_algorithm

    The nearest neighbour algorithm was one of the first algorithms used to solve the travelling salesman problem approximately. In that problem, the salesman starts at a random city and repeatedly visits the nearest city until all have been visited. The algorithm quickly yields a short tour, but usually not the optimal one.

  8. Good Neighbor Next Door program: What it is and how to apply

    www.aol.com/finance/good-neighbor-next-door...

    Key takeaways. The Good Neighbor Next Door Program offers qualifying buyers a chance to purchase a HUD-owned property for half off the list price and a down payment as low as $100.

  9. Voronoi diagram - Wikipedia

    en.wikipedia.org/wiki/Voronoi_diagram

    A point location data structure can be built on top of the Voronoi diagram in order to answer nearest neighbor queries, where one wants to find the object that is closest to a given query point. Nearest neighbor queries have numerous applications. For example, one might want to find the nearest hospital or the most similar object in a database.