Evaluating Models

Topics

• Evaluation

  • Need for model evaluation
  • Train-test split
  • Accuracy and error
  • Confusion matrix
  • Precision, recall and F1 score
  • Bias, transparency and accuracy concerns

Learning objectives

1. Build a confusion matrix and choose an appropriate metric to evaluate a classifier.