2. ANOMALY DETECTION
1. Causes of Outliers
i. Data errors:
ii. Normal variance in the data:
iii. Data from other distribution classes:
iv. Distributional assumptions:
3. Anomaly Detection Techniques
1. Outlier Detection Using Statistical Methods
1. Outlier Detection Using Data Mining
i. Distance based:
ii. Density based:
iii. Distribution based:
iv. Clustering:
v. Classification techniques: