IITM MLT Week 8 Questions
Naive Bayes Classification
Week 8 question PDF
Practice estimating class priors and class-conditional feature probabilities. Binary feature matrices and classification examples help connect the Naive Bayes independence assumption with numerical predictions.
The complete question statements, options, numerical data and any supporting graphs or tables are in the PDF. Numbered comprehension questions can include several subquestions. Answer keys are included for checking your attempt; these are not full worked solutions.
Topics covered in this collection
- Class priors and conditional probabilities
- Naive Bayes parameter estimation
- Conditional independence
- Classification and parameter counting
How to approach these questions
- Estimate a feature probability using examples from the relevant class, not the whole dataset.
- Combine the class prior with the conditional feature probabilities when comparing class scores.
- Account for probability constraints when counting independent parameters.
Attempt the questions using the assumptions and notation stated in each problem. For short-answer questions, round only at the final step to the requested precision. Check the provided key after solving and revisit the relevant concept when an answer differs.