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  2. Nearest-neighbor interpolation - Wikipedia

    en.wikipedia.org/wiki/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 ...

  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. Multivariate interpolation - Wikipedia

    en.wikipedia.org/wiki/Multivariate_interpolation

    Nearest-neighbor interpolation; Triangulated irregular network-based natural neighbor; Triangulated irregular network-based linear interpolation (a type of piecewise linear function) n-simplex (e.g. tetrahedron) interpolation (see barycentric coordinate system) Inverse distance weighting; ABOS - approximation based on smoothing; Kriging

  5. 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 ...

  6. 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.

  7. Bicubic interpolation - Wikipedia

    en.wikipedia.org/wiki/Bicubic_interpolation

    Colour indicates function value. The black dots are the locations of the prescribed data being interpolated. Note how the color samples are not radially symmetric. Bilinear interpolation on the same dataset as above. Derivatives of the surface are not continuous over the square boundaries. Nearest-neighbor interpolation on the same dataset as ...

  8. 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.

  9. 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. Formally, () = ‖ [] ‖, where [] is the mth closest to X 0 neighbor, and