Preprocess Data and Get Better Insights from Machine Learning Models

The main focus is on preprocessing and data visualization of machine learning models performances. Some functions allow to fill in gaps in time series using linear interpolation on panel data, some functions permit to draw lift effect and lift curve in order to benchmark machine learning models or you can even find the optimal number of clusters in agglomerative clustering algorithm.


Reference manual

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1.1.5 by Simon Corde, a year ago

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Browse source code at

Authors: Simon Corde [aut, cre]

Documentation:   PDF Manual  

GPL-3 license

Imports dplyr, ggplot2, sqldf, stringr, rlang, stats

Suggests devtools, testthat, covr

See at CRAN