Hi @rick-wheller ,
Can you provide more details about your use case? We have multiple unsupervised methods to detect anomalies built into the platform. Also, many of our blueprints use unsupervised methods (PCA, k-means clustering, etc.) to generate additional information for supervised models (e.g. XGBoost).
@rick-wheller No problem! We have isolation forest, one class SVM, and local outlier factor, and some other statistical techniques available.
One quick note: Isolation Forest and double median will perform the fastest on larger datasets.