[熱身賽第二輪] 評估分類系統(2) [Warm-up Round 2] Evaluating Classification Systems (2)

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教學主題 Topic
[熱身賽第二輪] 評估分類系統(2) [Warm-up Round 2] Evaluating Classification Systems (2)
其他模型 Others
Big Concept: Evaluating Classification Systems Topic: Why 99% Accuracy Can Still Be a Bad Model Bloom's Taxonomy: understand, apply, analyze, evaluate, remember Learning Goal: Use a confusion matrix to compare accuracy, precision, and recall, and judge whether a 99% accurate classifier is acceptable for spam filtering, fraud detection, or disease screening. Key Learning Points: confusion matrix; false positives vs. false negatives; precision; recall; task-dependent error cost
學生背景 Student Persona
Grade: 10th gradeFocus Time: 15 minutesBackground Knowledge: Has: percentages, ratios; Lacks: confusion matrices, precision, recall, and cost-sensitive evaluation.

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