Subword Features in Machine Learning for Text

This screencast demonstrates text classification with tidymodels by tokenizing post office names into subword features and training a linear support vector machine to identify Hawaii post offices. It also addresses class imbalance, resampling, evaluation metrics, and interpreting model coefficients.