Practice Train-Test Split - 12.5 | 12. Evaluation Methodologies of AI Models | CBSE Class 12th AI (Artificial Intelligence)
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12.5 - Train-Test Split

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Learning

Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What are the two main sets in a Train-Test Split?

💡 Hint: Think about what data you need to train the model and what data is needed to evaluate it.

Question 2

Easy

Why do we use only part of the dataset for training?

💡 Hint: Consider what would happen if we used the entire dataset for training.

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 technique do in AI?

  • Combines different datasets
  • Divides a dataset into training and testing parts
  • Only uses training data

💡 Hint: Consider what happens when preparing data for an AI model.

Question 2

True or False: Overfitting occurs when a model performs well on new data.

  • True
  • False

💡 Hint: Think about the consequences of excessive learning.

Solve 2 more questions and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

You are given a dataset with 10,000 observations. Design a splitting strategy to ensure that the training and testing datasets are representative of the overall distribution. Discuss your approach and justify your split ratios.

💡 Hint: Think about the diversity and distribution of your dataset.

Question 2

Evaluate the potential effects of using a very small testing set size (e.g., 5% of the total dataset) on the reliability of your model's evaluation. What are the risks, and how can they be mitigated?

💡 Hint: Consider what would happen if your testing data did not represent the different scenarios in your dataset.

Challenge and get performance evaluation