Correct Answer : Anomaly Detection
Explanation :
Outlier detection, often also referred to as Anomaly Detection, is the task to identify observations that deviate so much from other observations as to arouse suspicion that they were generated by a different mechanism (Hawkins, 1980).
In a frequently cited survey, Aggarwal (2015) categorized the types of outliers into three classes: (i) point outliers, (ii) collective outliers, and (iii) contextual outliers.
Specifically for temporal data, the review article by Gupta et al. (2014) highlights the two main types of outliers in time series data: (i) point outliers and (ii) subsequence outliers.
