pyproteonet.imputation.random_forest.random_forest_impute

pyproteonet.imputation.random_forest.random_forest_impute(dataset: Dataset, molecule: str, column: str, molecules_as_variables: bool = False, result_column: str | None = None, **kwargs) Dataset

Impute missing values using a random forest.

Parameters:
  • dataset (Dataset) – Dataset to impute.

  • molecule (str) – Molecule type to impute.

  • column (str) – Value column containing the missing values to impute.

  • molecules_as_variables (bool, optional) – Whether to transpose the input matrix before imputation. Defaults to False.

  • result_column (Optional[str], optional) – If given, name of the value column to store the imputed values in. Defaults to None.

Returns:

_description_

Return type:

Dataset