Explore examples of anomaly detection in data analysis and security, including identifying suspicious activities and deviations in patterns for enhanced insights and security measures.
Table of Contents
Question
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Statement 1: Forecasting housing prices based on historical data is an example of anomaly detection
Statement 2: Identifying suspicious sign-ins by looking for deviations from usual patterns is an example of anomaly detection
Statement 3: Predicting whether a patient will develop diabetes based on the patient’s medical history is an example of anomaly detection
Answer
Statement 1: Forecasting housing prices based on historical data is an example of anomaly detection: No
Statement 2: Identifying suspicious sign-ins by looking for deviations from usual patterns is an example of anomaly detection: Yes
Statement 3: Predicting whether a patient will develop diabetes based on the patient’s medical history is an example of anomaly detection: No
Explanation
Anomaly detection encompasses many important tasks in machine learning: Identifying transactions that are potentially fraudulent. Learning patterns that indicate that a network intrusion has occurred. Finding abnormal clusters of patients. Checking values entered into a system.
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