Classification Final Exam
Instructions:
- This final exam is worth 100 points.
- There are a total of 20 questions, each worth 5 points.
- Answer all questions to the best of your abilities.
- Write your answers clearly and concisely.
- Good luck!
1. Define classification and explain its importance in various fields.
2. What are the different types of classification systems?
3. Describe the process of hierarchical classification.
4. Explain the concept of feature selection in classification.
5. Discuss the difference between supervised and unsupervised classification.
6. What is the role of training data in classification algorithms?
7. Describe the k-nearest neighbors classification algorithm.
8. Explain how decision trees are used in classification.
9. Discuss the advantages and disadvantages of support vector machines.
10. What is the Naive Bayes classification algorithm? How does it work?
11. Explain the concept of ensemble learning in classification.
12. Discuss the applications of classification in real-world scenarios.
13. What is the confusion matrix in classification evaluation?
14. Explain the concept of precision and recall in classification evaluation.
15. Discuss the importance of cross-validation in classification model evaluation.
16. Describe the process of feature scaling in classification.
17. What is overfitting in classification models? How can it be prevented?
18. Explain the concept of hyperparameter tuning in classification algorithms.
19. Discuss the role of evaluation metrics in assessing the performance of classification models.
20. Describe a real-world example where classification has been successfully applied.
classification final exam
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