Precision, Recall, and F1 Score: The Confusion Matrix Explained With a Simple Disease Example
中文摘要
本文通过疾病案例解析混淆矩阵，解释精确率、召回率与F1分数，说明为何仅凭准确率无法评估模型好坏。
English Summary
Using a disease example, this article explains precision, recall, and F1 score to show why accuracy alone cannot determine a model's effectiveness.
Original Excerpt
Why “90% accurate” doesn’t always mean your model is good Continue reading on Medium »