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Test your understanding with targeted questions related to the topic.
Question 1
Easy
What is the primary objective of Logistic Regression?
π‘ Hint: Think about its name and what it's often used for.
Question 2
Easy
What does K in KNN stand for?
π‘ Hint: Related to how many 'neighbors' we look at.
Practice 4 more questions and get performance evaluation
Engage in quick quizzes to reinforce what you've learned and check your comprehension.
Question 1
What does Logistic Regression predict?
π‘ Hint: Think about its use case in classification.
Question 2
True or False: KNN builds a model during training.
π‘ Hint: Consider the definition of 'training' in predictive modeling.
Solve 2 more questions and get performance evaluation
Push your limits with challenges.
Question 1
You have a dataset with a severe class imbalance. Describe the steps you would take to prepare the data and choose evaluation metrics.
π‘ Hint: Consider the implications of using accuracy alone.
Question 2
Given that KNN is sensitive to irrelevant features, explain how you'd assess feature relevance before applying KNN.
π‘ Hint: Think about what constitutes a 'noisy' feature.
Challenge and get performance evaluation