Resultado de búsqueda
5.3.1 Vantage Point Tree •VPT es un árbol binario •Algoritmo de construcción Usar cualquier objeto p como raíz Calcular la mediana de todas las distancias a p Subárbol izquierdo: Subárbol derecho: Proceder recursivamente hasta que sólo haya un objeto en subárbol
A vantage-point tree (or VP tree) is a metric tree that segregates data in a metric space by choosing a position in the space (the "vantage point") and partitioning the data points into two parts: those points that are nearer to the vantage point than a threshold, and those points that are not.
Un VPT es un árbol binario en el que cada nodo representa un subconjunto S de individuos del conjunto inicial, utiliza un elemento especial del conjunto llamado pivote (vantage point) para dividir el conjunto S en dos subconjuntos, uno por cada hijo.
Vantage Point Trees. Based on “Data Structures and Algorithms for Nearest Neighbor Search in General Metric Spaces”, Peter N. Yianilos (1993) - http://algorithmics.lsi.upc.edu/docs/practicas/p311-yianilos.pdf. (Image from https://fribbels.github.io/vptree/writeup) Nearest Neighbor Search.
A vantage point tree (VP-Tree) is a data structure used for efficiently searching for nearest neighbors in metric spaces. It organizes data points in a tree structure based on their distances to a chosen vantage point. This enables faster search operations compared to traditional linear search methods.
The vp-tree (vantage point tree) is introduced in several forms, together with associated algorithms, as an improved method for these difficult search problems. Tree construction executes in time, and search is under certain circumstances and in the limit, expected time.
A vantage point tree implementation in OCaml. Cf. http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.41.4193&rep=rep1&type=pdf for details. A vantage point tree allows to do fast but exact nearest neighbor searches in any space provided that you have a distance function to measure the distance between any two points in that space.
