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5 cards from this section. Quick, good the night before a test.
What are the four components of a Confusion Matrix?
Remember the acronym TPFN.
In the context of spam detection, what would a False Positive mean?
Think about what happens when a legitimate message goes to spam.
What does a True Positive signify in a Confusion Matrix?
Think about what you are trying to identify as positive.
True or False: A False Negative indicates a correct positive prediction.
Consider if the prediction matches the reality.
You have a dataset for a medical diagnosis model with the following results: 45 True Positives, 5 False Positives, 30 False Negatives, and 20 True Negatives. Calculate the accuracy, precision, and recall. Discuss the implications if the precision is low.
Use the formulas consistently and consider the real-world impact of your results.
Interpret the following Confusion Matrix: TP: 150, FP: 20, FN: 30, TN: 800. What information does this provide regarding model performance, and what strategies could you employ to improve recall?
Reflect on how changing classification criteria can impact your model's performance.
6 more questions in this section. Enroll free to practise them all.
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