A collection of machine learning helper functions, particularly assisting in the Exploratory Data Analysis phase. Makes heavy use of the 'data.table' package for optimal speed and memory efficiency. Highlights include a versatile bin_data() function, sparsify() for converting a data.table to sparse matrix format with one-hot encoding, fast evaluation metrics, and empirical_cdf() for calculating empirical Multivariate Cumulative Distribution Functions.
|Date of publication||2017-07-11 00:30:06 UTC|
|Maintainer||Ben Gorman <bgorman@GormAnalysis.com>|
|License||MIT + file LICENSE|
|Package repository||View on CRAN|
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