Predict Astronauts' Mission Duration With Tidymodels and Bootstrap Aggregation

Learn how to implement bagging (bootstrap aggregating) in R using #TidyTuesday data on astronaut missions. Explore the dataset, analyze the data, build the data set, and create models using preprocessing, workflow, and bag models. Discover techniques for training multiple models, evaluating their performance, and renaming them for clarity. Follow along with the step-by-step process to predict astronauts' mission duration using tidymodels and bootstrap aggregation techniques.

Introduction
Dataset overview
Exploring the data
Analyzing the data
Building the data set
Modeling
Preprocessing
Workflow
Bag models
Add tree
Training 25 models
Evaluate models
Renaming models
Conclusion