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  2. R-tree - Wikipedia

    en.wikipedia.org/wiki/R-tree

    Simple example of an R-tree for 2D rectangles Visualization of an R*-tree for 3D points using ELKI (the cubes are directory pages) R-trees are tree data structures used for spatial access methods , i.e., for indexing multi-dimensional information such as geographical coordinates , rectangles or polygons .

  3. R*-tree - Wikipedia

    en.wikipedia.org/wiki/R*-tree

    In data processing R*-trees are a variant of R-trees used for indexing spatial information. R*-trees have slightly higher construction cost than standard R-trees, as the data may need to be reinserted; but the resulting tree will usually have a better query performance. Like the standard R-tree, it can store both point and spatial data.

  4. Hilbert R-tree - Wikipedia

    en.wikipedia.org/wiki/Hilbert_R-tree

    The performance of R-trees depends on the quality of the algorithm that clusters the data rectangles on a node. Hilbert R-trees use space-filling curves, and specifically the Hilbert curve, to impose a linear ordering on the data rectangles. There are two types of Hilbert R-trees: one for static databases, and one for dynamic databases. In both ...

  5. Rapidly exploring random tree - Wikipedia

    en.wikipedia.org/wiki/Rapidly_exploring_random_tree

    A rapidly exploring random tree (RRT) is an algorithm designed to efficiently search nonconvex, high-dimensional spaces by randomly building a space-filling tree.The tree is constructed incrementally from samples drawn randomly from the search space and is inherently biased to grow towards large unsearched areas of the problem.

  6. Priority R-tree - Wikipedia

    en.wikipedia.org/wiki/Priority_R-tree

    The term prioritized arrives from the introduction of four priority-leaves that represents the most extreme values of each dimensions, included in every branch of the tree. Before answering a window-query by traversing the sub-branches, the prioritized R-tree first checks for overlap in its priority nodes. The sub-branches are traversed (and ...

  7. Bump function - Wikipedia

    en.wikipedia.org/wiki/Bump_function

    The Fourier transform of a bump function is a (real) analytic function, and it can be extended to the whole complex plane: hence it cannot be compactly supported unless it is zero, since the only entire analytic bump function is the zero function (see Paley–Wiener theorem and Liouville's theorem).

  8. R+ tree - Wikipedia

    en.wikipedia.org/wiki/R+_tree

    An R+ tree is a method for looking up data using a location, often (x, y) coordinates, and often for locations on the surface of the Earth.Searching on one number is a solved problem; searching on two or more, and asking for locations that are nearby in both x and y directions, requires craftier algorithms.

  9. Symbolic regression - Wikipedia

    en.wikipedia.org/wiki/Symbolic_regression

    Expression tree as it can be used in symbolic regression to represent a function. Symbolic regression (SR) is a type of regression analysis that searches the space of mathematical expressions to find the model that best fits a given dataset, both in terms of accuracy and simplicity.