@@ -766,6 +766,9 @@ def add_dataset(
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E.g. `[negative, positive]` when `[0, 1]` are in your label column.
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label_column_name : str
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Column header in the csv containing the labels.
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+
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+ .. important::
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+ The labels in this column must be zero-indexed integer values.
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feature_names : List[str], default []
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List of input feature names. Only applicable if your ``task_type`` is
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:obj:`TaskType.TabularClassification` or :obj:`TaskType.TabularRegression`.
@@ -1056,12 +1059,15 @@ def add_dataframe(
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List of class names indexed by label integer in the dataset.
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E.g. `[negative, positive]` when `[0, 1]` are in your label column.
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label_column_name : str
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- Column header in the csv containing the labels.
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+ Column header in the dataframe containing the labels.
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+
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+ .. important::
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+ The labels in this column must be zero-indexed integer values.
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feature_names : List[str], default []
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List of input feature names. Only applicable if your ``task_type`` is
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:obj:`TaskType.TabularClassification` or :obj:`TaskType.TabularRegression`.
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text_column_name : str, default None
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- Column header in the csv containing the input text. Only applicable if your
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+ Column header in the dataframe containing the input text. Only applicable if your
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``task_type`` is :obj:`TaskType.TextClassification`.
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categorical_feature_names : List[str], default []
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A list containing the names of all categorical features in the dataframe.
@@ -1070,7 +1076,7 @@ def add_dataframe(
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commit_message : str, default None
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Commit message for this version.
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tag_column_name : str, default None
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- Column header in the csv containing tags you want pre-populated in Unbox.
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+ Column header in the dataframe containing tags you want pre-populated in Unbox.
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.. important::
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Each cell in this column must be either empty or contain a list of
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