Nonparametrically consistent depth-based classifiers

Details Nonparametrically consistent depth-based classifiers Nonparametrically consistent depth-based classifiers

2012-04-13

arxiv.org/abs/1204.2996v1

Mathematics

Statistics Theory

33 pages, 2 figures, 1 table

Scientific paper

We introduce a class of depth-based classification procedures that are of a nearest-neighbor nature. Depth, after symmetrization, indeed provides the center-outward ordering that is necessary and sufficient to define nearest neighbors. The resulting classifiers are affine-invariant and inherit the nonparametric validity from nearest-neighbor classifiers. In particular, we prove that the proposed depth-based classifiers are consistent under very mild conditions. We investigate their finite-sample performances through simulations and show that they outperform affine-invariant nearest-neighbor classifiers obtained through an obvious standardization construction. We illustrate the practical value of our classifiers on two real data examples. Finally, we shortly discuss the possible uses of our depth-based neighbors in other inference problems.

Affiliated with

Also associated with

No associations

Rating

Nonparametrically consistent depth-based classifiers does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Nonparametrically consistent depth-based classifiers, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Nonparametrically consistent depth-based classifiers will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-144189