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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
Name two key objectives of preparing data for classification.
💡 Hint: Think about the first steps before training a model.
Question 2
Easy
What is Logistic Regression mainly used for?
💡 Hint: Consider how this relates to decision making.
Practice 4 more questions and get performance evaluation
Interactive Quizzes
Engage in quick quizzes to reinforce what you've learned and check your comprehension.
Question 1
What does Logistic Regression predict?
- Continuous numbers
- Probabilities for classification
- Categorical values
💡 Hint: Think about the outcome of this regression technique.
Question 2
True or False: KNN uses a training phase to learn a model.
- True
- False
💡 Hint: Consider the nature of KNN as a lazy learner.
Solve 1 more question and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
Given a dataset with severe class imbalance, outline a detailed plan for preparing your data, selecting a model, and evaluating its effectiveness.
💡 Hint: Think about how you can mitigate issues arising from the class imbalance through your choice of metrics.
Question 2
Discuss how feature selection could potentially impact the performance of KNN in terms of the curse of dimensionality.
💡 Hint: Consider how too many features can dilute the meaning of 'closeness' in higher dimensions.
Challenge and get performance evaluation