base

Decide with a threshold derived from the observed score distribution.

Convert continuous scores into decisions or anomaly events.

Convert model outputs into standardized anomaly scores.

Score anomalies from distances to a learned normality boundary.

Decide by detecting distribution shifts in the score sequence.

Combine the scores of several child scorers into one score column.

Convert continuous scores into decisions or anomaly events.

Score anomalies directly on the observations without a model output.

Aggregate raw decisions into interval events with severity.

Score anomalies from estimated likelihoods.

Score anomalies from reconstruction errors.

Score anomalies from latent-space distances or densities.

Score anomalies from prediction or forecast residuals.

Convert model outputs into standardized anomaly scores.

Decide with a fixed, configured threshold.

Decide with statistical tests or control-chart rules.