📝 MCQ Test
Chapter 18 - Machine Learning Basics
1. Machine Learning is a subset of which field?
A. Artificial Intelligence
B. Word Processing
C. Computer Hardware
D. Desktop Publishing
2. What does a Machine Learning model learn from?
A. Monitor size
B. Data
C. Keyboard colour
D. Printer speed
3. Which learning method uses labelled data?
A. Clustering
B. Unsupervised learning
C. Supervised learning
D. Reinforcement learning
4. Which learning method discovers patterns in unlabelled data?
A. Supervised learning
B. Regression only
C. Classification only
D. Unsupervised learning
5. Which learning method uses rewards and penalties?
A. Reinforcement learning
B. Supervised learning
C. Word processing
D. File management
6. Which task predicts a category such as spam or non-spam?
A. Regression
B. Classification
C. Formatting
D. Clustering only
7. Which task predicts a numerical value?
A. Classification
B. Sorting
C. Regression
D. File compression
8. What is training data used for?
A. To clean the monitor
B. To format a document
C. To increase screen resolution
D. To help a model learn patterns
9. What is the purpose of testing data?
A. To evaluate a trained model
B. To train the keyboard
C. To install an operating system
D. To create folders
10. What is clustering?
A. Deleting duplicate files
B. Grouping similar data points
C. Printing a report
D. Translating a document
11. What is a feature in Machine Learning?
A. The final report only
B. A type of printer
C. An input variable used by a model
D. A computer cable
12. What is a label in supervised learning?
A. A monitor setting
B. A programming error
C. A storage device
D. The expected output for an example
13. What is overfitting?
A. Learning training data too closely and generalizing poorly
B. Learning nothing from data
C. Deleting the training dataset
D. Improving every prediction automatically
14. What is underfitting?
A. A model that memorizes all training examples
B. A model that fails to learn important patterns
C. A perfectly accurate model
D. A type of keyboard
15. Which is an example of Machine Learning in daily life?
A. Changing a monitor cable
B. Opening a text editor
C. Email spam detection
D. Switching on a light
16. Why should a model be tested on unseen data?
A. To make the dataset larger automatically
B. To remove every possible error
C. To guarantee perfect accuracy
D. To assess its ability to generalize
17. Which factor can reduce Machine Learning model reliability?
A. Poor-quality or biased data
B. Relevant training examples
C. Appropriate testing
D. Careful evaluation
18. Which technique groups similar customers without predefined labels?
A. Supervised classification
B. Clustering
C. Word processing
D. Regression only
19. What is the role of a Machine Learning algorithm?
A. To replace all computer hardware
B. To print every dataset
C. To learn patterns or train a model
D. To increase screen brightness
20. Which statement about Machine Learning is correct?
A. It always produces perfect results
B. It never needs data
C. It cannot make mistakes
D. Its predictions may be wrong and should be evaluated
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