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3 cards from this section. Quick, good the night before a test.
What does KNN stand for?
Recall the main term used in the algorithm.
What is meant by majority voting in KNN?
Think about how votes are counted.
What does the K in KNN represent?
Think about what the algorithm needs to decide the classes.
True or False: KNN assumes a normal distribution of data.
Consider the flexibility of KNN in working with data.
You are given a dataset with features that are on different scales. How would you ensure KNN performs effectively on this data?
Consider how distance is measured in KNN.
Define a scenario where KNN might not perform well, and explain why.
Think about how distance behaves in more than three dimensions.
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