Resultado de búsqueda
21 de jul. de 2021 · Una de las estructuras de datos que nos facilita reducir de manera drástica el tiempo de búsqueda (concretamente, de O(n) a O(log n)) es el VP-Tree, cuyo nombre completo en inglés es Vantage-point Trees y, en español, Árboles de Punto de Ventaja.
Vantage-Point Tree. This is a data structure which is a representative of another class of trees — ball trees. It is really similar to the k-d tree in the way it works and has similar complexity but it uses circles instead of lines to form the left and right subtree.
Among these, vantage point tree (vp-tree) was introduced for information retrieval in metric spaces. Vp-trees have recently shown very good performances for image patch retrieval with respect to the L metric. In this paper we generalize the seminal vp-tree construction and search algo-rithms to the broader class of Bregman divergences.
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.
VP-Tree (Vantage Point Tree) is a data structure that enables efficient nearest neighbor search in metric spaces, with applications in machine learning, computer vision, and information retrieval.
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.
5.3.1 Vantage Point Tree •Heurística propuesta para elegir p: escoger objetos “lejos” del resto •Algoritmo de búsqueda, consultas por rango Calcular Si d ≤ r, añadir p al resultado Si d – r ≤ M, buscar recursivamente en subárbol izquierdo Si d + r > M, buscar recursivamente en subárbol derecho
