1. In predictive maintenance of rotating machinery, predicting the remaining
useful life (RUL) of a bearing is an example of:
a) Classification
b) Regression
c) Clustering
d) Association
2. Detecting defective components in a production line (defective / non-
defective) is a:
a) Regression problem
b) Clustering problem
c) Classification problem
d) Association problem
3. Which metric is most suitable to evaluate temperature prediction in a heat
exchanger system?
a) Accuracy
b) Precision
c) RMSE
d) Recall
4. K-means algorithm is mainly used for:
a) Regression
b) Classification
c) Clustering
d) Outlier removal
5. Which learning type uses labeled vibration data from machines?
a) Unsupervised learning
b) Semi-supervised learning
c) Supervised learning
d) Reinforcement learning
6. Identifying unusual vibration signals in a turbine is an example of:
a) Clustering
b) Regression
c) Outlier detection
d) Association rule mining
7. Which of the following is a regression algorithm?
a) Random Forest
b) Logistic Regression
c) Linear Regression
d) K-means
8. DBSCAN is mainly used for:
a) Regression
b) Clustering
c) Classification
d) Feature scaling
9. In model training, splitting data into training and test sets helps to:
a) Increase data size
b) Reduce features
c) Evaluate model performance
d) Remove outliers
10.Which metric combines precision and recall?
a) Accuracy
