Practice Leave-One-Out Cross-Validation (LOOCV) - 12.3.D | 12. Model Evaluation and Validation | Data Science Advance
K12 Students

Academics

AI-Powered learning for Grades 8–12, aligned with major Indian and international curricula.

Academics
Professionals

Professional Courses

Industry-relevant training in Business, Technology, and Design to help professionals and graduates upskill for real-world careers.

Professional Courses
Games

Interactive Games

Fun, engaging games to boost memory, math fluency, typing speed, and English skillsβ€”perfect for learners of all ages.

games

Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What does LOOCV stand for?

πŸ’‘ Hint: Think about what each point in the dataset represents in this technique.

Question 2

Easy

How many iterations does LOOCV perform on a dataset of 5 points?

πŸ’‘ Hint: Each point gets a turn as the test set.

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 LOOCV stand for?

  • Leave-One-Out Cross-Validation
  • Last-One-Out Cross-Validation
  • Leave-Some-Out Cross-Validation

πŸ’‘ Hint: Think about what it means to leave one out!

Question 2

LOOCV has high computational costs compared to k-fold cross-validation.

  • True
  • False

πŸ’‘ Hint: Consider how many times the model is trained compared to k-fold.

Solve 1 more question and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

A company has collected 30 samples of customer data. If they wish to use LOOCV to evaluate their predictive model, calculate how many times the model needs to be trained.

πŸ’‘ Hint: Remember, LOOCV trains on all but one sample each time.

Question 2

Discuss the implications of using LOOCV for a dataset with 10,000 samples in terms of time and computational resources.

πŸ’‘ Hint: Think about resource allocation and the cost-effectiveness of model validation.

Challenge and get performance evaluation