# tfma.evaluators.AnalysisTableEvaluator

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| [![](https://www.tensorflow.org/images/GitHub-Mark-32px.png) View source on GitHub](https://github.com/tensorflow/model-analysis/blob/v0.46.0/tensorflow_model_analysis/evaluators/analysis_table_evaluator.py#L25-L65) |

Creates an Evaluator for returning Extracts data for analysis.

    tfma.evaluators.AnalysisTableEvaluator(
        key: str = constants.ANALYSIS_KEY,
        run_after: str = extractor.LAST_EXTRACTOR_STAGE_NAME,
        include: Optional[Union[Iterable[str], Dict[str, Any]]] = None,
        exclude: Optional[Union[Iterable[str], Dict[str, Any]]] = None
    ) -> https://www.tensorflow.org/tfx/model_analysis/api_docs/python/tfma/evaluators/Evaluator

If both include and exclude are None then tfma.INPUT_KEY extracts will be
excluded by default.

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| ## Args ||
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| `key` | Name to use for key in Evaluation output. |
| `run_after` | Extractor to run after (None means before any extractors). |
| `include` | List or map of keys to include in output. Keys starting with '_' are automatically filtered out at write time. If a map of keys is passed then the keys and sub-keys that exist in the map will be included in the output. An empty dict behaves as a wildcard matching all keys or the value itself. Since matching on feature values is not currently supported, an empty dict must be used to represent the leaf nodes. For example: {'key1': {'key1-subkey': {} }, 'key2': {} }. |
| `exclude` | List or map of keys to exclude from output. If a map of keys is passed then the keys and sub-keys that exist in the map will be excluded from the output. An empty dict behaves as a wildcard matching all keys or the value itself. Since matching on feature values is not currently supported, an empty dict must be used to represent the leaf nodes. For example: {'key1': {'key1-subkey': {} }, 'key2': {} }. |

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| ## Returns ||
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| Evaluator for collecting analysis data. The output is stored under the key 'analysis'. ||

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| ## Raises ||
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| `ValueError` | If both include and exclude are used. |

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