Confusion Matrix, Accuracy, Recall, Precision.
Confusion metrics provide a comprehensive evaluation of the performance of classification models, allowing us to measure accuracy, precision, recall, specificity, and the F1 score. By understanding and interpreting these metrics, we gain valuable insights into a model’s effectiveness. In this blog