A treeless absolutely random forest with closed‐form estimators of expected proximities
Eugene Laska,
Ziqiang Lin,
Carole Siegel
et al.
Abstract:We introduce a simple variant of a purely random forest, called an absolute random forest (ARF) used for clustering. At every node, splits of units are determined by a randomly chosen feature and a random threshold drawn from a uniform distribution whose support, the range of the selected feature in the root node, does not change. This enables closed‐form estimators of parameters, such as pairwise proximities, to be obtained without having to grow a forest. The probabilistic structure corresponding to an ARF i… Show more
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