tfma.view.render_slicing_metrics

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Renders the slicing metrics view as widget.

tfma.view.render_slicing_metrics(
    result: tfma.EvalResult,
    slicing_column: Optional[str] = None,
    slicing_spec: Optional[Union[slicer.SingleSliceSpec, tfma.SlicingSpec]] = None,
    weighted_example_column: Optional[str] = None,
    event_handlers: Optional[Callable[[Dict[str, Union[str, float]]], None]] = None
) -> Optional[visualization.SlicingMetricsViewer]

Used in the notebooks

Used in the tutorials
TensorFlow Model Analysis TFX Estimator Component Tutorial TFX Keras Component Tutorial Create a TFX pipeline for your data with Penguin template Model analysis using TFX Pipeline and TensorFlow Model Analysis

Args
result	An tfma.EvalResult.
slicing_column	The column to slice on.
slicing_spec	The tfma.SlicingSpec to filter results. If neither column nor spec is set, show overall.
weighted_example_column	Override for the weighted example column. This can be used when different weights are applied in different aprts of the model (eg: multi-head).
event_handlers	The event handlers

Returns
A SlicingMetricsViewer object if in Jupyter notebook; None if in Colab.