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CGMissingDataR

CGMissingDataR is an R package based on the CGMissingData Python library for evaluating model performance under feature missingness by:

• injecting missing values into feature columns at specified masking rates,
• imputing missing values using a Multiple Imputation by Chained Equations (MICE)-style iterative imputer, and
• training Random Forest and k-Nearest Neighbors regressors to report Mean ABsolute Percentage Error (MAPE) and R across missingness levels.

Before the installation, ensure that you have the following R packages installed:

install.packages(c("FNN", "ranger", "mice"))

Install the development version of CGMissingDataR from GitHub:

devtools::install_github("saraswatsh/CGMissingDataR")

Vignette

A brief vignette illustrating the usage of CGMissingDataR can be found here.

Changelog

The changelog is available here.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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