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databricks.labs.dqx.anomaly.model_discovery

Discover model columns, segments, and quantile points from the anomaly registry.

get_record_for_discovery​

def get_record_for_discovery(registry_client: AnomalyModelRegistry,
                             registry_table: str,
                             model_name_local: str) -> AnomalyModelRecord

Get model record for auto-discovery, checking global and segmented models.

select_segment_record​

def select_segment_record(
        all_segments: list[AnomalyModelRecord]) -> AnomalyModelRecord

Select a deterministic segment record (latest training_time, tie-breaker by model_name).

get_quantile_points_for_severity​

def get_quantile_points_for_severity(
        record: AnomalyModelRecord) -> list[tuple[float, float]]

Extract percentile->score points for severity mapping.

Used internally for scoring and exposed for testing and advanced use.

extract_quantile_points​

def extract_quantile_points(
        record: AnomalyModelRecord) -> list[tuple[float, float]]

Extract percentile->score points for severity mapping.

fetch_model_columns_and_segments​

def fetch_model_columns_and_segments(
        df: DataFrame, model_name: str,
        registry_table: str) -> tuple[list[str], list[str] | None]

Auto-discover columns and segmentation from the model registry.

Returns:

Tuple of (columns, segment_by).