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An implementation of an algorithm for outlier detection that can handle a) data with a mixed categorical and continuous variables, b) many columns of data, c) many rows of data, d) outliers that mask other outliers, and e) both unidimensional and multidimensional datasets. Unlike ad hoc methods found in many machine learning papers, HDoutliers is based on a distributional model that uses probabilities to determine outliers. See
Package details 


Author  Chris Fraley [aut, cre], Leland Wilkinson [ctb] 
Date of publication  20161224 11:23:58 
Maintainer  Chris Fraley <[email protected]> 
License  MIT + file LICENSE 
Version  0.15 
URL  https://www.rproject.org https://www.cs.uic.edu/~wilkinson/Publications/outliers.pdf 
Package repository  View on CRAN 
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