There are many methods for detecting and optionally remove outliers from a dataset. However, four of the most frequently used methods for outlier detection are Z-Score (a parametric outlier detection technique), Numeric Outlier, DBSCAN, and Isolation Forest (non-parametric methods). DBSCAN and Isolation Forest are used for large datasets.