Package: preprosim
Type: Package
Title: Lightweight Data Quality Simulation for Classification
Version: 0.1.0
Date: 2016-05-28
Authors@R: person("Markus", "Vattulainen", email = "markus.vattulainen@gmail.com", role = c("aut", "cre"))
Description: Data quality simulation can be used to check the robustness of data
    analysis findings and learn about the impact of data quality contaminations on
    classification. This package helps to add contaminations (noise, missing values,
    outliers, low variance, irrelevant features, class swap (inconsistency), class
    imbalance and decrease in data volume) to data and then evaluate the simulated
    data sets for classification accuracy. As a lightweight solution simulation runs
    can be set up with no or minimal up-front effort.
License: GPL-2
LazyData: TRUE
Imports: DMwR, reshape2, ggplot2, methods, stats, caret, doParallel,
        foreach
Suggests: gbm, testthat, preprocomb, preproviz, knitr, rmarkdown
URL: https://github.com/mvattulainen/preprosim
BugReports: https://github.com/mvattulainen/preprosim/issues
VignetteBuilder: knitr
RoxygenNote: 5.0.1
NeedsCompilation: no
Packaged: 2016-05-28 04:39:33 UTC; Markus
Author: Markus Vattulainen [aut, cre]
Maintainer: Markus Vattulainen <markus.vattulainen@gmail.com>
Repository: CRAN
Date/Publication: 2016-05-28 08:18:24
