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2 cards from this section. Quick, good the night before a test.
What is the formula for calculating accuracy?
Think about how correct predictions are comprised.
Can accuracy be misleading? Why?
Consider a scenario where one class dominates the dataset.
What is the formula for accuracy?
Think about the correct predictions versus all observations.
True or False: Accuracy can effectively evaluate models in imbalanced datasets.
Consider how class distribution can skew the metrics.
Imagine a situation where you have a model with an accuracy of 97%, but 90% of the data goes to a trivial class. Discuss the implications.
Consider the balance between the classes in your evaluation.
Evaluate a model with the following confusion matrix: TP = 200, TN = 50, FP = 10, FN = 5. Calculate the accuracy and discuss whether it's a reliable metric.
Compute accurately, then reflect on class distributions.
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