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  2. Inverse distance weighting - Wikipedia

    en.wikipedia.org/wiki/Inverse_distance_weighting

    Inverse Distance Weighting as a sum of all weighting functions for each sample point. Each function has the value of one of the samples at its sample point and zero at every other sample point. Inverse distance weighting ( IDW ) is a type of deterministic method for multivariate interpolation with a known scattered set of points.

  3. Natural-neighbor interpolation - Wikipedia

    en.wikipedia.org/wiki/Natural-neighbor_interpolation

    Natural neighbor interpolation with Sibson weights. The area of the green circles are the interpolating weights, w i.The purple-shaded region is the new Voronoi cell, after inserting the point to be interpolated (black dot).

  4. Multivariate interpolation - Wikipedia

    en.wikipedia.org/wiki/Multivariate_interpolation

    Inverse distance weighting; ABOS - approximation based on smoothing; Kriging; Gradient-enhanced kriging (GEK) Thin plate spline; Polyharmonic spline (the thin-plate-spline is a special case of a polyharmonic spline) Radial basis function (Polyharmonic splines are a special case of radial basis functions with low degree polynomial terms) Least ...

  5. List of numerical analysis topics - Wikipedia

    en.wikipedia.org/wiki/List_of_numerical_analysis...

    Inverse distance weighting; Radial basis function (RBF) — a function of the form ƒ(x) = φ(|x−x 0 |) Polyharmonic spline — a commonly used radial basis function; Thin plate spline — a specific polyharmonic spline: r 2 log r; Hierarchical RBF; Subdivision surface — constructed by recursively subdividing a piecewise linear interpolant

  6. Kernel method - Wikipedia

    en.wikipedia.org/wiki/Kernel_method

    For many algorithms that solve these tasks, the data in raw representation have to be explicitly transformed into feature vector representations via a user-specified feature map: in contrast, kernel methods require only a user-specified kernel, i.e., a similarity function over all pairs of data points computed using inner products.

  7. k-nearest neighbors algorithm - Wikipedia

    en.wikipedia.org/wiki/K-nearest_neighbors_algorithm

    Compute the Euclidean or Mahalanobis distance from the query example to the labeled examples. Order the labeled examples by increasing distance. Find a heuristically optimal number k of nearest neighbors, based on RMSE. This is done using cross validation. Calculate an inverse distance weighted average with the k-nearest multivariate neighbors.

  8. Spatial weight matrix - Wikipedia

    en.wikipedia.org/wiki/Spatial_weight_matrix

    The concept of a spatial weight is used in spatial analysis to describe neighbor relations between regions on a map. [1] If location i {\displaystyle i} is a neighbor of location j {\displaystyle j} then w i j ≠ 0 {\displaystyle w_{ij}\neq 0} otherwise w i j = 0 {\displaystyle w_{ij}=0} .

  9. Thin plate spline - Wikipedia

    en.wikipedia.org/wiki/Thin_plate_spline

    Elastic map (a discrete version of the thin plate approximation for manifold learning) Inverse distance weighting; Polyharmonic spline (the thin plate spline is a special case of a polyharmonic spline) Radial basis function; Smoothing spline; Spline; Subdivision surface (emerging alternative to spline-based surfaces)