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.

Getting started

Package details

AuthorMarkus Vattulainen [aut, cre]
MaintainerMarkus Vattulainen <markus.vattulainen@gmail.com>
LicenseGPL-2
Version0.2.0
URL https://github.com/mvattulainen/preprosim
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("preprosim")

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preprosim documentation built on May 1, 2019, 6:27 p.m.