RPEnsemble: Random Projection Ensemble Classification

Implements the methodology of "Cannings, T. I. and Samworth, R. J. (2015) Random projection ensemble classification. http://arxiv.org/abs/1504.04595". The random projection ensemble classifier is a very general method for classification of high-dimensional data, based on careful combination of the results of applying an arbitrary base classifier to random projections of the feature vectors into a lower-dimensional space. The random projections are divided into non-overlapping blocks, and within each block the projection yielding the smallest estimate of the test error is selected. The random projection ensemble classifier then aggregates the results of applying the base classifier on the selected projections, with a data-driven voting threshold to determine the final assignment.

Version: 0.2
Depends: R (≥ 3.0.0), MASS
Imports: class, parallel, stats
Published: 2015-05-08
Author: Timothy I. Cannings and Richard J. Samworth
Maintainer: Timothy I. Cannings <t.cannings at statslab.cam.ac.uk>
License: GPL-3
URL: http://arxiv.org/abs/1504.04595, http://www.statslab.cam.ac.uk/~tc325/
NeedsCompilation: no
CRAN checks: RPEnsemble results


Reference manual: RPEnsemble.pdf
Package source: RPEnsemble_0.2.tar.gz
Windows binaries: r-devel: RPEnsemble_0.2.zip, r-release: RPEnsemble_0.2.zip, r-oldrel: RPEnsemble_0.2.zip
OS X Snow Leopard binaries: r-release: RPEnsemble_0.2.tgz, r-oldrel: RPEnsemble_0.2.tgz
OS X Mavericks binaries: r-release: RPEnsemble_0.2.tgz
Old sources: RPEnsemble archive