1. What is anomaly detection primarily used for?
(A) Identifying unusual patterns or outliers
(B) Predicting continuous values
(C) Classifying labeled data
(D) Reducing data dimensions
2. Which of the following is another name for anomaly detection?
(A) Regression analysis
(B) Data normalization
(C) Feature engineering
(D) Outlier detection
3. Which anomaly detection technique assumes data follows a Gaussian distribution?
(A) K-Means
(B) Isolation Forest
(C) DBSCAN
(D) Z-score method
4. Which type of anomaly is a single unusual data point?
(A) Contextual anomaly
(B) Point anomaly
(C) Collective anomaly
(D) Sequential anomaly
5. Which algorithm is commonly used for unsupervised anomaly detection?
(A) Decision Tree
(B) Isolation Forest
(C) Naive Bayes
(D) Linear Regression
6. Which method detects anomalies by isolating observations?
(A) KNN
(B) Linear Regression
(C) Isolation Forest
(D) Logistic Regression
7. What does an anomaly score represent?
(A) Degree of abnormality
(B) Probability of being normal
(C) Accuracy of the model
(D) Mean of dataset
8. Which anomaly depends on context (time, location, season)?
(A) Point anomaly
(B) Global anomaly
(C) Contextual anomaly
(D) Collective anomaly
9. Which clustering algorithm is often used for anomaly detection?
(A) DBSCAN
(B) Apriori
(C) KNN
(D) PCA
10. In anomaly detection, what is a false positive?
(A) Normal point labeled as normal
(B) Normal point labeled as anomaly
(C) Anomaly correctly detected
(D) Anomaly missed by model
11. Which technique reduces dimensionality before detecting anomalies?
(A) PCA
(B) K-Means
(C) Decision Tree
(D) Logistic Regression
12. What is the main challenge in anomaly detection?
(A) Large amount of labeled anomalies
(B) High frequency of anomalies
(C) Low computational cost
(D) Imbalanced data
13. Which metric is commonly used to evaluate anomaly detection models?
(A) Accuracy
(B) R-squared
(C) Precision and Recall
(D) Mean Absolute Error
14. Which anomaly detection method is distance-based?
(A) KNN-based detection
(B) Z-score
(C) Isolation Forest
(D) Autoencoder
15. What type of learning is most anomaly detection?
(A) Unsupervised
(B) Reinforcement
(C) Supervised
(D) Semi-supervised
16. Which deep learning model is used for anomaly detection?
(A) CNN
(B) RNN
(C) SVM
(D) Autoencoder
17. What does contamination parameter indicate in anomaly detection?
(A) Number of features
(B) Sample size
(C) Learning rate
(D) Percentage of anomalies
18. Which anomaly occurs as a group of abnormal points?
(A) Point anomaly
(B) Contextual anomaly
(C) Global anomaly
(D) Collective anomaly
19. Which method is best for detecting anomalies in time-series data?
(A) LSTM-based models
(B) K-Means
(C) Linear Regression
(D) Naive Bayes
20. Which statement about anomalies is TRUE?
(A) Anomalies occur frequently
(B) Anomalies are rare events
(C) Anomalies are always noise
(D) Anomalies improve model accuracy