Source code for etna.analysis.feature_relevance.utils

from typing import Tuple

import numpy as np
import pandas as pd

[docs]def _get_fictitious_relevances(pvalues: pd.DataFrame, alpha: float) -> Tuple[np.ndarray, float]: """ Convert p-values into fictitious variables, with function f(x) = 1 - x. Also converts alpha into fictitious variable. Parameters ---------- pvalues: dataFrame with pvalues alpha: significance level, default alpha = 0.05 Returns ------- pvalues: array with fictitious relevances new_alpha: adjusted significance level """ pvalues = 1 - pvalues new_alpha = 1 - alpha return pvalues, new_alpha