Welcome to your Machine Learning Quizzes 2024 This quiz has multiple choice questions and each has only one correct answer.
Total Questions : 25
To pass this quiz you need to score 80% or above.
Time Provided : 45 minutes
Today's Date : 28 May 2025
All the best!!
Name
Email
1. In a simple linear regression model, what is the equation used to predict the dependent variable y?
2. Which of the following methods can be used to estimate the parameters of a linear regression model?
3. What does the coefficient "m" represent in the linear regression equation y=mx+b?
4. What is the equation of the logistic function used in logistic regression?
5. What is a leaf node in a decision tree?
6. Which of the following metrics is commonly used to evaluate the performance of a logistic regression model?
7. Which of the following is a common regularization technique used in logistic regression to prevent overfitting?
8. Which of the following metrics is commonly used to measure the goodness of fit in a linear regression model?
9. In logistic regression, what is the purpose of the threshold value?
10. Which of the following is the logistic regression model used for?
11. Which of the following techniques can be used to check for multicollinearity?
12. What type of problems are decision trees typically used for?
13. What is the purpose of the y-intercept "b" in the linear regression equation y=mx+b?
14. Which of the following methods can be used to estimate the parameters in logistic regression?
15. What does an odds ratio greater than 1 indicate in logistic regression?
16. In the context of logistic regression, what is multicollinearity?
17. Which of the following is the main objective of linear regression?
18. What type of dependent variable is used in logistic regression?
19. In decision trees, what is the information gain used for?
20. What is multicollinearity in the context of multiple linear regression?
21. What is overfitting in the context of decision trees?
22. Which criterion is commonly used to split nodes in a decision tree for classification?
23. Which assumption is NOT required for linear regression analysis?
24. What is a decision node in a decision tree?
25. In the context of linear regression, what does a residual represent?
