RCF3 documentation¶

rcf3 exposes the following public detector families:

• Forest API: Random Cut Forest for numerical streaming data, including anomaly scores, attribution, neighborhood search, imputation, forecasting, and serialization
• OnlineIForest API: Online Isolation Forest for numerical streams with sliding-window updates and preview scoring
• MStream API: mixed numerical/categorical streaming anomaly detection with logical timestamps and decomposed scores
• FeatureSketch API: sparse feature-name anomaly detection for streams whose schema can grow or shrink over time

Start with the guide that matches the shape of your data:

• choose Forest for numerical observations and the full RCF feature set
• choose OnlineIForest for a compact numerical detector with update-after-learning scores
• choose MStream when events combine numerical and categorical aspects
• choose FeatureSketch when each event is a sparse set of named features and the feature universe is not fixed