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3 cards from this section. Quick, good the night before a test.
What does the term True Positive (TP) refer to?
Think about when the model performs effectively in identifying positive cases.
How would you define accuracy?
It's a measure of overall effectiveness.
What is the formula for calculating accuracy?
Remember all components included in the accuracy calculation.
True or False: Recall is also known as sensitivity.
Think about terms used interchangeably in the context of model evaluation.
An AI model predicts loan approvals with the following results: 100 actual approvals, 80 correct predictions, 20 incorrect predictions due to false negatives. Calculate the recall.
Reference the definition of recall and ensure you identify TP and FN accurately.
A model exhibits high precision but low recall. Discuss potential ramifications of this imbalance.
Think about the implications of prioritizing one metric over another in practical applications.
6 more questions in this section. Enroll free to practise them all.
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