TidyX 56: XGBoost for pitchf/x classification

Building on the previous weeks, Ellis Hughes and I work on pitchf/x classification using the popular XGBoost algorithm.

We discuss:

  • The basics of XGBoost
  • Training an XGBoost model
  • Evaluating the variables of importance within the model
  • Tuning model parameters of an XGBoost model using the {caret} package

To watch our screen cast, CLICK HERE.

To access our code, CLICK HERE.

For previous episodes in this classification series:

  1. Episode 53: Pitch Classification & EDA
  2. Episode 54: KNN & UMAP
  3. Episode 55: Decision Trees, Random Forest, & Optimization