compute_improvement_outlier_correction#
- pepbench.data_handling.compute_improvement_outlier_correction(data: DataFrame, outlier_algos: Sequence[str]) DataFrame[source]#
Compute the percentage of samples which improved, deteriorated, or remained unchanged after outlier correction.
- Parameters:
- data
pandas.DataFrame The data containing the PEP values before and after outlier correction.
- outlier_algoslist of str
The outlier correction algorithms to consider.
- data
- Returns:
pandas.DataFrameThe percentage of samples which improved, deteriorated, or remained unchanged after outlier correction.
- Raises:
- ValidationError
If the input data is not a
pandas.DataFrame.