This article is about the data structure. For the type of metric space, see Real tree.
A metric tree is any tree data structure specialized to index data in metric spaces. Metric trees exploit properties of metric spaces such as the triangle inequality to make accesses to the data more efficient. Examples include the M-tree, vp-trees, cover trees, MVP trees, and BK-trees.[1]
^Samet, Hanan (2006). Foundations of multidimensional and metric data structures. Morgan Kaufmann. ISBN 978-0-12-369446-1.
A metrictree is any tree data structure specialized to index data in metric spaces. Metrictrees exploit properties of metric spaces such as the triangle...
a ball tree, balltree or metrictree, is a space partitioning data structure for organizing points in a multi-dimensional space. A ball tree partitions...
introduced by Mikhael Gromov, generalizes the metric properties of classical hyperbolic geometry and of trees. Hyperbolicity is a large-scale property, and...
In mathematics, a metric space is a set together with a notion of distance between its elements, usually called points. The distance is measured by a function...
branch-and-bound approach is known as the metrictree approach. Particular examples include vp-tree and BK-tree methods. Using a set of points taken from...
mathematics, real trees (also called R {\displaystyle \mathbb {R} } -trees) are a class of metric spaces generalising simplicial trees. They arise naturally...
inequality. This variant is known as the metric Steiner tree problem. Given an instance of the (non-metric) Steiner tree problem, we can transform it in polynomial...
underlying metric, the performance of various heuristic algorithms for decision tree learning may vary significantly. A simple and effective metric can be...
the metric space. Each level C is associated with an integer value i that decrements by one as the tree is descended. Each level C in the cover tree has...
Moringa oleifera is a fast-growing, drought-resistant tree of the family Moringaceae, native to the Indian subcontinent and used extensively in South and...
effectiveness of the decision tree using some key metrics that will be discussed in the evaluating a decision tree section below. The metrics that will be discussed...
Claypool. Uhlmann published seminal papers on volumetric, spatial, and metrictree data structures and their applications for computer graphics, virtual...
intervals distinct, the metric makes them equivalent by assigning them 0 distance. Hedgehog spaces are examples of real trees. The metric on the plane in which...
approaches based on the choice of metric and algorithm. Metrics include: Fano metric Zigangirov metric Gallager metric Algorithms include: Stack algorithm...
A phylogenetic tree, phylogeny or evolutionary tree is a graphical representation which shows the evolutionary history between a set of species or taxa...
phylogenetic tree. Let x be the lowest common ancestor between two species i and j, we expect Mij = Mix + Mxj. This is where the additive metric comes from...
inheritance tree; and (6) lack of cohesion of methods. Several other metrics can be used to measure programming complexity: Branching complexity (Sneed Metric) Data...
mature tree with a crown diameter measuring 15 metres (49 ft) absorbed 28.5 metric tons (28.0 long tons; 31.4 short tons) of CO2 annually. The trees have...
Euclidean TSP is much easier than the general metric case for approximation. For example, the minimum spanning tree of the graph associated with an instance...
of indexing algorithms have been presented. Among them are suffix trees, metrictrees and n-gram methods. A detailed survey of indexing techniques that...
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