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Louis Pouillot
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Correct docstring
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dataikuapi/apinode_client.py

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@@ -26,8 +26,7 @@ def predict_record(self, endpoint_id, features, forced_generation=None, dispatch
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:param forced_generation: See documentation about multi-version prediction
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:param dispatch_key: See documentation about multi-version prediction
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:param context: Optional, Python dictionary of additional context information. The context information is logged, but not directly used.
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:param with_explanations: Whether individual explanations should be computed for each records.
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Explanations must be enabled for the prediction endpoint.
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:param with_explanations: Optional, whether individual explanations should be computed for each records. The prediction endpoint must be compatible.
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:param explanation_method: Optional, method to compute those explanations. If None, will use the value configured in the endpoint.
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:param n_explanations: Optional, number of explanations to output per prediction. If None, will use the value configured in the endpoint.
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:param n_explanations_mc_steps: Optional, precision parameter for SHAPLEY method, higher means more precise but slower (between 25 and 400).
@@ -63,8 +62,7 @@ def predict_records(self, endpoint_id, records, forced_generation=None, dispatch
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:param records: Python list of records. Each record must be a Python dict. Each record must contain a "features" dict (see predict_record) and optionally a "context" dict.
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:param forced_generation: See documentation about multi-version prediction
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:param dispatch_key: See documentation about multi-version prediction
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:param with_explanations: Whether individual explanations should be computed for each records.
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Explanations must be enabled for the prediction endpoint.
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:param with_explanations: Optional, whether individual explanations should be computed for each records. The prediction endpoint must be compatible.
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:param explanation_method: Optional, method to compute those explanations. If None, will use the value configured in the endpoint.
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:param n_explanations: Optional, number of explanations to output per prediction. If None, will use the value configured in the endpoint.
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:param n_explanations_mc_steps: Optional, precision parameter for SHAPLEY method, higher means more precise but slower (between 25 and 400).

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