0 of 15 Questions completed
Questions:
You have already completed the quiz before. Hence you can not start it again.
Quiz is loading…
You must sign in or sign up to start the quiz.
You must first complete the following:
0 of 15 Questions answered correctly
Your time:
Time has elapsed
You have reached 0 of 0 point(s), (0)
Earned Point(s): 0 of 0, (0)
0 Essay(s) Pending (Possible Point(s): 0)
What does LightGBM stand for?
How does LightGBM differ from traditional gradient boosting methods in terms of speed and efficiency?
What is the analogy used to describe LightGBM in the article?
Which technique in LightGBM is used to select data instances for training that yield a larger gain?
How does LightGBM handle the growth of trees compared to GBM and XGBoost?
What is the main advantage of LightGBM in terms of handling large datasets?
What is the purpose of regularization in LightGBM?
Which gradient boosting algorithm is known for its ability to handle sparse data and missing values?
What is a limitation of LightGBM when dealing with small datasets?
What is the main advantage of LightGBM in terms of speed and efficiency?
Which technique in LightGBM is used to reduce the dimension of the feature space?
What does the F1-score measure in a classification report?
Which algorithm is considered the basic form of gradient boosting?
What is a limitation of LightGBM in terms of interpretability?
Which algorithm is known for being the most computationally efficient and fast among GBM, XGBoost, and LightGBM?
Unlock AI & Data Science treasures. Log in!