The following tables summarize the advised use cases for the current algorithms. Please consult the method specific pages for a more detailed breakdown of each method. The column Feature Level indicates whether the outlier scoring and detection can be done and returned at the feature level, e.g. per pixel for an image.
|Detector|Tabular|Image|Time Series|Text|Categorical Features|Online|Feature Level| |---|---|---|---|---| |Isolation Forest|✔|✘|✘|✘|✔|✘|✘| |Mahalanobis Distance|✔|✘|✘|✘|✔|✔|✘| |AE|✔|✔|✘|✘|✘|✘|✔| |VAE|✔|✔|✘|✘|✘|✘|✔| |AEGMM|✔|✔|✘|✘|✘|✘|✘| |VAEGMM|✔|✔|✘|✘|✘|✘|✘| |Likelihood Ratios|✔|✔|✔|✘|✔|✘|✔| |Prophet|✘|✘|✔|✘|✘|✘|✘| |Spectral Residual|✘|✘|✔|✘|✘|✔|✔| |Seq2Seq|✘|✘|✔|✘|✘|✘|✔|
|Detector|Tabular|Image|Time Series|Text|Categorical Features|Online|Feature Level| |---|---|---|---|---| |Adversarial AE|✔|✔|✘|✘|✘|✘|✘|
|Detector|Tabular|Image|Time Series|Text|Categorical Features|Online|Feature Level| |---|---|---|---|---| |Kolmogorov-Smirnov|✔|✔|✘|✔|✔|✔|✔| |Maximum Mean Discrepancy|✔|✔|✘|✔|✔|✘|✘|