Escaping the curse of dimensionality with a tree-based regressor
Annual Conference Computational Learning Theory (COLT), 2009
Abstract
We present the first tree-based regressor whose convergence rate depends only on the intrinsic dimension of the data, namely its Assouad dimension. The regressor uses the RPtree partitioning procedure, a simple randomized variant of k-d trees.
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