The result of a single model analysis run.
tfma.EvalResult(
    slicing_metrics,
    plots,
    attributions,
    config,
    data_location,
    file_format,
    model_location
)
| Attributes | 
|---|
| slicing_metrics | a list of tfma.SlicedMetrics, containing metric values
for each slice. | 
| plots | List of slice-plot pairs. | 
| attributions | List of SlicedAttributions containing attribution values for
each slice. | 
| config | The config containing slicing and metrics specification. | 
| data_location | Optional location for data used with config. | 
| file_format | Optional format for data used with config. | 
| model_location | Optional location(s) for model(s) used with config. | 
Methods
get_attributions_for_all_slices
View source
get_attributions_for_all_slices(
    metric_name: str = '',
    output_name: str = '',
    class_id: Optional[int] = None,
    k: Optional[int] = None,
    top_k: Optional[int] = None
) -> Dict[str, AttributionsByFeatureKey]
Get attribution feature keys and values for every slice.
| Args | 
|---|
| metric_name | Name of metric to get attributions for. Optional if only one
metric used. | 
| output_name | The name of the output (optional, only used for multi-output
models). | 
| class_id | Used with multi-class metrics to identify a specific class ID. | 
| k | Used with multi-class metrics to identify the kth predicted value. | 
| top_k | Used with multi-class and ranking metrics to identify top-k
predicted values. | 
| Returns | 
|---|
| Dictionary mapping slices to attribution feature keys and values. | 
get_attributions_for_slice
View source
get_attributions_for_slice(
    slice_name: slicer.SliceKeyType = (),
    metric_name: str = '',
    output_name: str = '',
    class_id: Optional[int] = None,
    k: Optional[int] = None,
    top_k: Optional[int] = None
) -> Union[AttributionsByFeatureKey, None]
Get attribution features names and values for a slice.
| Args | 
|---|
| slice_name | A tuple of the form (column, value), indicating which slice to
get attributions from. Optional; if excluded, use overall slice. | 
| metric_name | Name of metric to get attributions for. Optional if only one
metric used. | 
| output_name | The name of the output. Optional, only used for multi-output
models. | 
| class_id | Used with multi-class models to identify a specific class ID. | 
| k | Used with multi-class models to identify the kth predicted value. | 
| top_k | Used with multi-class models to identify top-k attribution values. | 
| Returns | 
|---|
| Dictionary containing feature keys and values for the specified slice. | 
| Raises | 
|---|
| ValueError | If metric_name is required. | 
get_metric_names
View source
get_metric_names() -> Sequence[str]
Get names of metrics.
| Returns | 
|---|
| List of metric names. | 
get_metrics_for_all_slices
View source
get_metrics_for_all_slices(
    output_name: str = '',
    class_id: Optional[int] = None,
    k: Optional[int] = None,
    top_k: Optional[int] = None
) -> Dict[str, MetricsByTextKey]
Get metric names and values for every slice.
| Args | 
|---|
| output_name | The name of the output (optional, only used for multi-output
models). | 
| class_id | Used with multi-class metrics to identify a specific class ID. | 
| k | Used with multi-class metrics to identify the kth predicted value. | 
| top_k | Used with multi-class and ranking metrics to identify top-k
predicted values. | 
| Returns | 
|---|
| Dictionary mapping slices to metric names and values. | 
get_metrics_for_slice
View source
get_metrics_for_slice(
    slice_name: slicer.SliceKeyType = (),
    output_name: str = '',
    class_id: Optional[int] = None,
    k: Optional[int] = None,
    top_k: Optional[int] = None
) -> Union[MetricsByTextKey, None]
Get metric names and values for a slice.
| Args | 
|---|
| slice_name | A tuple of the form (column, value), indicating which slice to
get metrics from. Optional; if excluded, return overall metrics. | 
| output_name | The name of the output. Optional, only used for multi-output
models. | 
| class_id | Used with multi-class metrics to identify a specific class ID. | 
| k | Used with multi-class metrics to identify the kth predicted value. | 
| top_k | Used with multi-class and ranking metrics to identify top-k
predicted values. | 
| Returns | 
|---|
| Dictionary containing metric names and values for the specified slice. | 
get_slice_names
View source
get_slice_names() -> Sequence[str]
Get names of slices.
| Returns | 
|---|
| List of slice names. |