Author jean-pierreBoth
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Updated Last
3 Years Ago
Started In
March 2020

a julia implementation of Random Projection Tree Classifier

The implementation follows the papers of Das Gupta and Freund.


The data are first stored in a root node of a tree. Then a binary tree is created by propagating data down to leaves according to random projection and a sphericity constrains inside nodes. We thus get a collection of $2^{d}$ leaves if d is the depth of the tree asked for.


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  1. DasGupta S. Freund Y. Random projection trees for vector quantization 2009.
  2. DasGupta S. Freund Y. Random projection trees and low dimensional manifolds 2007.

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