Practice Train-test Split (6.5.2.1.5) - Introduction to Deep Learning (Weeks 12)
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Train-Test Split

Practice - Train-Test Split

Learning

Practice Questions

Test your understanding with targeted questions

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.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

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.

2 more questions available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

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.

Challenge 2 Hard

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.

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Reference links

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