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  "Title": "Random Projection Ensemble Classification",
  "Author": "Timothy I. Cannings and Richard J. Samworth",
  "Maintainer": "Timothy I. Cannings <timothy.cannings@ed.ac.uk>",
  "Description": "Implements the methodology of \"Cannings, T. I. and\nSamworth, R. J. (2017) Random-projection ensemble\nclassification, J. Roy. Statist. Soc., Ser. B. (with\ndiscussion), 79, 959--1035\". The random projection ensemble\nclassifier is a general method for classification of\nhigh-dimensional data, based on careful combination of the\nresults of applying an arbitrary base classifier to random\nprojections of the feature vectors into a lower-dimensional\nspace. The random projections are divided into non-overlapping\nblocks, and within each block the projection yielding the\nsmallest estimate of the test error is selected. The random\nprojection ensemble classifier then aggregates the results of\napplying the base classifier on the selected projections, with\na data-driven voting threshold to determine the final\nassignment.",
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  "URL": "https://arxiv.org/abs/1504.04595,\nhttps://www.maths.ed.ac.uk/~tcannings/",
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