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4 cards from this section. Quick, good the night before a test.
Define accuracy in your own words.
Think about the ratio of correct predictions.
What does True Positive mean?
Consider what 'positive' means in the context of predictions.
What is the formula for accuracy?
Recall this formula when considering the number of true and false predictions.
True or False: High accuracy always means a model is performing well.
Think about how class distribution affects this statement.
A model has 120 true positives, 80 true negatives, 50 false positives, and 50 false negatives. Calculate its accuracy and determine if the accuracy reflects good model performance given the context of class distribution.
Reassess the implications of accuracy in light of balanced vs. imbalanced datasets.
Design a brief evaluation framework for a model predicting heart disease. Discuss why accuracy might not be your primary metric.
Think about what happens if a sick person is fails to be identified.
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