tfma.metrics.QueryStatistics

Query statistic metrics.

Inherits From: Metric

tfma.metrics.QueryStatistics(
    total_queries_name: str = TOTAL_QUERIES_NAME,
    total_documents_name: str = TOTAL_DOCUMENTS_NAME,
    min_documents_name: str = MIN_DOCUMENTS_NAME,
    max_documents_name: str = MAX_DOCUMENTS_NAME
)

These metrics are query/ranking based so a query_key must also be provided in the associated metrics spec.

total_queries_name Total queries metric name.
total_documents_name Total documents metric name.
min_documents_name Min documents name.
max_documents_name Max documents name.

compute_confidence_interval Whether to compute confidence intervals for this metric.

Note that this may not completely remove the computational overhead involved in computing a given metric. This is only respected by the jackknife confidence interval method.

Methods

computations

View source

computations(
    eval_config: Optional[tfma.EvalConfig] = None,
    schema: Optional[schema_pb2.Schema] = None,
    model_names: Optional[List[str]] = None,
    output_names: Optional[List[str]] = None,
    sub_keys: Optional[List[Optional[SubKey]]] = None,
    aggregation_type: Optional[AggregationType] = None,
    class_weights: Optional[Dict[int, float]] = None,
    example_weighted: bool = False,
    query_key: Optional[str] = None
) -> tfma.metrics.MetricComputations

Creates computations associated with metric.

from_config

View source

@classmethod
from_config(
    config: Dict[str, Any]
) -> 'Metric'

get_config

View source

get_config() -> Dict[str, Any]

Returns serializable config.