preprosim: Lightweight Data Quality Simulation for Classification

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.

Install the latest version of this package by entering the following in R:
install.packages("preprosim")
AuthorMarkus Vattulainen [aut, cre]
Date of publication2016-07-26 12:14:58
MaintainerMarkus Vattulainen <markus.vattulainen@gmail.com>
LicenseGPL-2
Version0.2.0
https://github.com/mvattulainen/preprosim

View on CRAN

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

Please suggest features or report bugs with the GitHub issue tracker.

All documentation is copyright its authors; we didn't write any of that.