RPEnsemble: Random Projection Ensemble Classification

Timothy Cannings (Developer), Richard Samworth (Developer)

Research output: Non-textual formSoftware

Abstract

Implements the methodology of "Cannings, T. I. and Samworth, R. J. (2017) Random-projection ensemble classification, J. Roy. Stat. Soc., Ser. B. (with discussion), 79, 959–1035". The random projection ensemble classifier is a 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.
Original languageEnglish
PublisherCRAN - The Comprehensive R Archive Network
Edition0.4
Publication statusPublished - 7 Oct 2017

Fingerprint Dive into the research topics of 'RPEnsemble: Random Projection Ensemble Classification'. Together they form a unique fingerprint.

Cite this