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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What is the purpose of the Train-Test Split?
💡 Hint: Think about preventing overfitting.
Question 2
Easy
What is overfitting?
💡 Hint: Consider how memorization affects learning.
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 the Train-Test Split aim to accomplish?
- A) To increase the dataset size
- B) To assess model performance on new data
- C) To ensure the model memorizes the training data
💡 Hint: Consider the purpose of splitting data.
Question 2
True or False: Overfitting occurs when a model performs poorly on both training and test data.
- True
- False
💡 Hint: Think about how training affects new data performance.
Solve 2 more questions and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
Given a heavily imbalanced dataset of 10,000 instances with 9,000 belonging to class A and 1,000 to class B, what strategies would you use when applying the Train-Test Split to ensure reliable performance evaluation?
💡 Hint: Focus on equal representation in both sets.
Question 2
You have a dataset of 500 instances and decide to split it using a simple Train-Test Split with a 90/10 ratio. Discuss the potential impacts this might have on your performance metrics and the validity of your evaluation.
💡 Hint: Consider the significance of sample size on reliability.
Challenge and get performance evaluation