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Small documentation clarification
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dataikuapi/dss/ml.py

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@@ -599,10 +599,10 @@ def compute_subpopulation_analyses(self, split_by, wait=True, sample_size=1000,
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"""
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Launch computation of Subpopulation analyses for this trained model.
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:param list split_by: columns on which subpopulation analyses are to be computed
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:param bool wait: if True, the call blocks until the run is finished and returns the results
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:param list split_by: columns on which subpopulation analyses are to be computed (one analysis per column)
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:param bool wait: if True, the call blocks until the computation is finished and returns the results directly
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:param int sample_size: number of records of the dataset to use for the computation
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:param int random_state: random state to use to build sample. Ensure reproducibility
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:param int random_state: random state to use to build sample, for reproducibility
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:param int n_jobs: number of cores used for parallel training. (-1 means 'all cores')
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:param bool debug_mode: if True, output all logs (slower)
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@@ -659,9 +659,9 @@ def compute_partial_dependencies(self, features, wait=True, sample_size=1000, ra
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Launch computation of Partial dependencies for this trained model.
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:param list features: features on which partial dependencies are to be computed
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:param bool wait: if True, the call blocks until the run is finished and returns the results
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:param bool wait: if True, the call blocks until the computation is finished and returns the results directly
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:param int sample_size: number of records of the dataset to use for the computation
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:param int random_state: random state to use to build sample. Ensure reproducibility
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:param int random_state: random state to use to build sample, for reproducibility
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:param int n_jobs: number of cores used for parallel training. (-1 means 'all cores')
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:param bool debug_mode: if True, output all logs (slower)
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