Help protect the Great Barrier Reef with TensorFlow on Kaggle Join Challenge

tfma.evaluators.AnalysisTableEvaluator

Creates an Evaluator for returning Extracts data for analysis.

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

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': {} }.

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

ValueError If both include and exclude are used.