Machine Learning Basics
JKSSB Sub-Inspector (Telecommunication) · Artificial Intelligence, Data Science & Automation · 18 practice questions with answers and explanations: 9 Easy, 9 Medium, 0 Hard.
Sample questions
Sample Easy question 1
In machine learning, what are 'features'?
- The programming language
- The input variables used to make a prediction
- The computer's hardware
- The final answer
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Answer: B. Features describe each example, such as size or age.
Sample Easy question 2
A model correctly predicts 40 true positives and 45 true negatives, with 5 false positives and 10 false negatives. What is its accuracy?
- 80%
- 90%
- 88.9%
- 85%
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Answer: D. Accuracy = (TP + TN)/total = (40 + 45)/100 = 85%.
Sample Easy question 3
Which kind of neural network is designed for sequential data such as text or time series?
- Self-organising grid
- Convolutional neural network (CNN)
- Recurrent neural network (RNN)
- Feed-forward network with no memory alone
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Answer: C. RNNs keep a hidden state that carries information along the sequence.
Sample Medium question 4
Which kind of neural network is widely used for image recognition?
- Decision stump
- Naive lookup table
- Convolutional neural network (CNN)
- Linear regression
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Answer: C. CNNs learn spatial patterns such as edges and shapes.
Sample Medium question 5
Using TP = 40, FP = 5, FN = 10, what is the precision?
- 80%
- 50%
- 85%
- 88.9%
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Answer: D. Precision = TP/(TP + FP) = 40/45 ≈ 88.9%.
Sample Medium question 6
Using TP = 40, FP = 5, FN = 10, what is the recall?
- 85%
- 80%
- 88.9%
- 40%
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Answer: B. Recall = TP/(TP + FN) = 40/50 = 80%.