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I am really excited to announce my beta package and it is now available to download on GitHub.

This is my third package I have managed to create. I have many more projects, tutorials and code snippets available on my GitHub site.

I hope you find it useful and read below to find out how to install it, work with it and get the most out of it.

## How to use the package?

The package guidance, and installation, can be found on the GitHub site directly, but to install the package follow the below steps:

library(ggplot)
# install.packages("remotes") # if not already installed
remotes::install_github("https://github.com/StatsGary/ConfusionTableR")
library(ConfusionTableR)


The vignette is avaialble for easy reference and will allow you to understand the process step by step.

## Motivation for the package

The package aim is to make it easier to convert the outputs of the lists from caret and collapse these down into row-by-row entries, specifically designed for storing the outputs in a database or row by row data frame.

This is something that the CARET library does not have as a default and I have designed this to allow the confusion matrix outputs to be stored in a data frame or database, as many a time we want to track the ML outputs and fits over time to monitor feature slippage and changes in the underlying patterns of the data.

## What’s included in the package?

The package contains three really useful functions:

• BinaryFramer – this is to convert the elements of carets confusionMatrix() object into a database storable format
• MultiFramer – this is to convert a mutli classification matrix output into a database storable format
• BinaryVisualiseR – this creates a confusion matrix visualisation, currently only for binary classification tasks:

## What’s next for the package?

I plan to keep working on this package to get it pushed up to CRAN, however there is no reason to stop you using this right away.

## Feedback and testing

To enable any bugs to be fixed as soon as possible, then please make sure issues are raised on GitHub.

## Closing remarks

I hope you find this package useful and please don’t hesitate to contact me directly if you want to collaborate or suggest new ideas for the package.