Implements the methodology of "Cannings, T. I. and Samworth, R. J. (2017) Randomprojection ensemble classification, J. Roy. Stat. Soc., Ser. B. (with discussion), 79, 9591035". The random projection ensemble classifier is a general method for classification of highdimensional data, based on careful combination of the results of applying an arbitrary base classifier to random projections of the feature vectors into a lowerdimensional space. The random projections are divided into nonoverlapping 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 datadriven voting threshold to determine the final assignment.
Package details 


Author  Timothy I. Cannings and Richard J. Samworth 
Maintainer  Timothy I. Cannings <cannings@marshall.usc.edu> 
License  GPL3 
Version  0.4 
URL  http://arxiv.org/abs/1504.04595 http://wwwbcf.usc.edu/~cannings/ 
Package repository  View on CRAN 
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