If you want to train machine learning models, R offers thousands of packages to try out. However, most of these are written by random students and academics, so they are not proper standardized. It can looks like this: So, it's a nightmare trying out a lot of models or (learning) algorithms to predict a specific outcome of interest. What we really need is a kind of meta-model package that wraps the others for you, and has a standardized interface. There are such packages, mainly people have been using caret for years. However, caret is not part of tidyverse and is quite old, so Max Kuhn decided to make a new version for
Trying out tidymodels package
Trying out tidymodels package
Trying out tidymodels package
If you want to train machine learning models, R offers thousands of packages to try out. However, most of these are written by random students and academics, so they are not proper standardized. It can looks like this: So, it's a nightmare trying out a lot of models or (learning) algorithms to predict a specific outcome of interest. What we really need is a kind of meta-model package that wraps the others for you, and has a standardized interface. There are such packages, mainly people have been using caret for years. However, caret is not part of tidyverse and is quite old, so Max Kuhn decided to make a new version for