Exercise

UMAP reduction in a decision tree model

Now that you have visualized a UMAP reduction, let's put UMAP to work in model building. In this exercise, you will build a workflow that applies UMAP in a preprocessing recipe to the credit data and then use the extracted components to build a decision tree model. The credit data train and test sets are provided for you. The embed library has already been loaded.

Instructions

100 XP
  • Create a recipe to apply a UMAP reduction to the data, resulting in four extracted components.
  • Create a decision_tree model for classification.
  • Add the UMAP recipe and the decision tree model to a workflow.