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Tabular Parameters

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Tabular Parameters

class autotrain.trainers.tabular.params.TabularParams

< >

( data_path: str = None model: str = 'xgboost' username: Optional = None seed: int = 42 train_split: str = 'train' valid_split: Optional = None project_name: str = 'project-name' token: Optional = None push_to_hub: bool = False id_column: str = 'id' target_columns: Union = ['target'] categorical_columns: Optional = None numerical_columns: Optional = None task: str = 'classification' num_trials: int = 10 time_limit: int = 600 categorical_imputer: Optional = None numerical_imputer: Optional = None numeric_scaler: Optional = None )

Parameters

  • data_path (str) — Path to the dataset.
  • model (str) — Name of the model to use. Default is “xgboost”.
  • username (Optional[str]) — Hugging Face Username.
  • seed (int) — Random seed for reproducibility. Default is 42.
  • train_split (str) — Name of the training data split. Default is “train”.
  • valid_split (Optional[str]) — Name of the validation data split.
  • project_name (str) — Name of the output directory. Default is “project-name”.
  • token (Optional[str]) — Hub Token for authentication.
  • push_to_hub (bool) — Whether to push the model to the hub. Default is False.
  • id_column (str) — Name of the ID column. Default is “id”.
  • target_columns (Union[List[str], str]) — Target column(s) in the dataset. Default is [“target”].
  • categorical_columns (Optional[List[str]]) — List of categorical columns.
  • numerical_columns (Optional[List[str]]) — List of numerical columns.
  • task (str) — Type of task (e.g., “classification”). Default is “classification”.
  • num_trials (int) — Number of trials for hyperparameter optimization. Default is 10.
  • time_limit (int) — Time limit for training in seconds. Default is 600.
  • categorical_imputer (Optional[str]) — Imputer strategy for categorical columns.
  • numerical_imputer (Optional[str]) — Imputer strategy for numerical columns.
  • numeric_scaler (Optional[str]) — Scaler strategy for numerical columns.

TabularParams is a configuration class for tabular data training parameters.

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