Practice Implement Boosting: Gradient Boosting Machines (GBM) - 4.5.4 | Module 4: Advanced Supervised Learning & Evaluation (Weeks 7) | Machine Learning
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

Define what is meant by 'Residual' in the context of GBM.

πŸ’‘ Hint: Think about what the model gets wrong in its predictions.

Question 2

Easy

What does the learning rate control in a GBM?

πŸ’‘ Hint: It affects how quickly or slowly the model learns.

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 GBM stand for?

  • General Boosting Machines
  • Gradient Boosting Machines
  • Gaussian Boosting Machines

πŸ’‘ Hint: Think about which term emphasizes 'gradient'.

Question 2

True or False: GBM uses parallel learning.

  • True
  • False

πŸ’‘ Hint: Consider how each model learns from the previous one.

Solve 1 more question and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

Design a simple scenario where GBM would outperform a single decision tree. Provide reasoning for your answer.

πŸ’‘ Hint: Think about complexity in data relationships.

Question 2

How would you approach tuning the learning rate and the number of trees in GBM for a dataset with high variance?

πŸ’‘ Hint: Balance is key in tuning; reflect on the bias-variance trade-off.

Challenge and get performance evaluation