Machine Learning

Question 1

What is class imbalance in supervised machine learning?

Answer 1

Class imbalance occurs when the number of instances in one class is significantly higher or lower than in other classes in a dataset.

Question 2

True or False: Class imbalance can lead to biased models that favor the majority class.

Answer 2

True

Question 3

Fill in the blank: Techniques such as _____ and _____ are commonly used to address class imbalance.

Answer 3

oversampling, undersampling

Question 4

What is the purpose of balancing classes in a supervised learning model?

Answer 4

The purpose is to ensure that the model learns equally from all classes, improving its performance and generalization.

Question 5

Which of the following is NOT a method to address class imbalance? A) SMOTE B) Random undersampling C) Adding noise to the dataset D) Cost-sensitive learning

Answer 5

C) Adding noise to the dataset