A machine learning evaluation metric that measures the proportion of actual positive samples that the model correctly identifies as positive. It is calculated as true positives divided by the sum of true positives and false negatives. Recall is especially important in scenarios where missing a positive case (such as failing to detect a defective product) carries a high cost.

Past questions testing this term · 1 questions

• 2023r05 #76品質管理担当者が行っている検査を自動化することを考えた。10,000枚の製品画像と、それに対する品質管理担当者による不良品かどうかの判定結果を学習データとして与…