andrewdisher / multinomial-logistic-regression

An R markdown notebook detailing the necessary steps to fit a multinomial logistic regression model to some sample data.

Fitting Multinomial Logistic Regression Model in R

This is a repository for my statistical modelling endeavor to fit a multinomial logistic regression model to the fetal health data set, available on Kaggle here: Fetal Health Classification. You can also find the data within the data folder of this repository.

Goals

• Practice fitting the multinomial logistic regression model
• Practice balancing data sets via over/under-sampling class stratified observations
• Applying Principal Component Analysis (PCA) to a set of predictors/features
• Use visualizations and computed metrics to assess model fit
• Practice using the box package for explicit package and function dependencies (instead of using library() calls)

Viewing the Notebook

There are two options:

1. Download this repository and knit the R Markdown document locally
2. Use this link to view the github.io website hosted from this repository: Notebook Link

A Note on renv

renv is an R package that provides a way to track packages, their package dependencies, and the versions for these packages. It makes creating a reproducible R coding environment extremely easy and ensures that the packages used will always stay the same, even when future releases are announced.

After downloading this repository and opening the R project, you must run this line of code in your R r console:

renv::restore(clean = TRUE)

This will use the renv.lock file to restore the project environment. After that, you should be able to knit the R Markdown document as usual.