Logistic Regression
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Machine Learning
Probabilistic Modeling
Interview questions on Probabilistic Modeling.
23 questions
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Logistic Regression
Q2. What is the main assumption of logistic regression?
Logistic Regression
Q3. Write the expression of sigmoid or logistic function?
Logistic Regression
Q4. Prove that logistic regression is a linear classifier?
Logistic Regression
Q5. Does closed-form solution exists for logistic regression?
Logistic Regression
Q6. How can we learn the parameters of logistic regression model?
Logistic Regression
Q7. State the difference between Naive bayes and Logistic regression model?
Logistic Regression
Q8. What is the range of logistic(sigmoid function)?
Logistic Regression
Q9. What is the difference between Conditional MLE and standard MLE, and how does it relate to logistic regression?
Logistic Regression
Q10. What is the issue with using squared losses(MSE) or absolute losses(MAE) for logistic regression model?
Logistic Regression
Q11. Can we use logistic regression for multiclass classification problem?
Logistic Regression
Q12. Write the expression of softmax function?
Logistic Regression
Q13. State one issue with softmax function over sigmoid?
Logistic Regression
Q14. How is Maximum Likelihood Estimation (MLE) used in logistic regression, and why is it preferred over other estimation methods like least squares?
Logistic Regression
Q15. What is Maximum A Posteriori (MAP) Estimation in logistic regression?
Logistic Regression
Q16. How does MAP differ from Maximum Likelihood Estimation (MLE) in logistic regression?
Logistic Regression
Q17. What role do priors play in MAP estimation?
Logistic Regression
Q18. Why might MAP be preferred over MLE in logistic regression?
Logistic Regression
Q19. How does MAP help in small datasets compared to MLE?
Logistic Regression
Q20. What type of priors are commonly used in MAP for logistic regression?
Logistic Regression
Q21. How does MAP provide flexibility compared to MLE?
Logistic Regression
Q22. What is the main advantage of using MAP in logistic regression?
Logistic Regression