Multi-class Model Evaluation with Confusion Matrix and Classification Report

Model Evaluation

Precision, Recall, F1, Micro, Macro, Weighted, and Classification Report

If you are familiar with the Confusion Matrix, you might know that it is mainly explained for binary classification, which has only two outputs. TP, TN, FP, FN, and other derived metrics like precision and recall are convenient to understand. However, it is not the same case when we have more than two target classes.

In this blog, Focus will be on the problem with more …

classification data science deep learning evaluation evaluation-metric machine learning python report