qolmat.benchmark.missing_patterns.GroupedHoleGenerator¶
- class qolmat.benchmark.missing_patterns.GroupedHoleGenerator(n_splits: int, subset: Optional[List[str]] = None, ratio_masked: float = 0.05, random_state: Optional[Union[int, RandomState]] = None, groups: Tuple[str, ...] = ())[source]¶
GroupedHoleGenerator class.
This class implements a way to generate holes in a dataframe. The holes are generated from groups, specified by the user.
- Parameters
- n_splitsint
Number of splits
- subsetOptional[List[str]], optional
Names of the columns for which holes must be created, by default None
- ratio_maskedOptional[float], optional
Ratio of masked to add, by default 0.05
- random_stateint, RandomState instance or None, default=None
Controls the randomness. Pass an int for reproducible output across multiple function calls.
- groupsTuple[str, …]
Names of the columns forming the groups, by default []
- __init__(n_splits: int, subset: Optional[List[str]] = None, ratio_masked: float = 0.05, random_state: Optional[Union[int, RandomState]] = None, groups: Tuple[str, ...] = ())[source]¶
- fit(X: DataFrame) GroupedHoleGenerator[source]¶
Create the groups based on the column names (groups attribute).
- Parameters
- Xpd.DataFrame
input dataframe
- Returns
- GroupedHoleGenerator
The model itself
- Raises
- if the number of samples/splits is greater than the number of groups.
