Artifacts using RQuery (2)
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Supplies higher-order coordinatized data specification and fluid transform operators that include pivot and anti-pivot as special cases. The methodology is describe in 'Zumel', 2018, "Fluid data reshaping with 'cdata'", <http://winvector.github.io/FluidData/FluidDataReshapingWithCdata.html> , doi:10.5281/zenodo.1173299 . This package introduces the idea of control table specification of data transforms (later also adapted from 'cdata' by 'tidyr'). Works on in-memory data or on remote data using 'rquery' and ...
Last Release on May 1, 2022
A 'data.frame' processor/conditioner that prepares real-world data for predictive modeling in a statistically sound manner. 'vtreat' prepares variables so that data has fewer exceptional cases, making it easier to safely use models in production. Common problems 'vtreat' defends against: 'Inf', 'NA', too many categorical levels, rare categorical levels, and new categorical levels (levels seen during application, but not during training). Reference: "'vtreat': a data.frame Processor for Predictive Modeling", ...
Last Release on Feb 13, 2021