Orthogonal Range Queries: Range Trees and Kd-Trees (2/6) | Computational Geometry - Lecture 05

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Computational Geometry
Lecture 05: Orthogonal Range Queries: Range Trees and Kd-Trees
Part II: Kd-Trees: Construction
Philipp Kindermann

  1. Philipp Kindermann
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Комментарии
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Your way of visualizing and explaining these algorithms is really easy to follow and understand. Saved me big time in algorithm analysis class.

dolphinos
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Our (i.e. at my university) algorithm was a little different. We used [..., m+1] and [m-1, ...] for the points that are still to be sorted in - effectively excluding the median for future iterations. Also we drew lines so that every point had a line in the end. Not sure if those are just minor alterations, but just in case someone else stumbles upon this.

theelysium
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Can you explain KD tree for paragraph matching

mahnoorasif
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Welchen Median nimmt man? Den bezüglich der Anzahl der Punkte oder den bezüglich der Werte in x-/ y- Koordinate? Was macht man bei einer geraden Anzahl von Punkten wie 10, der Median wäre 5, 5? Ich habe mehrere Videos zu k d Bäumen gefunden, manche teilen die Ebenen durch Punkte und manche ziehen wirklich den Median der gegebenen Werte.

nchm