tabensemb.trainer.Trainer.get_approx_cv_leaderboard#

method

Trainer.get_approx_cv_leaderboard(leaderboard: DataFrame, save: bool = True) Tuple[DataFrame, DataFrame][source]#

Calculate approximated averages and standard errors based on cross_validation() results in the folder self.project_root/cv.

Parameters:
leaderboard

A reference leaderboard to be filled by avg and std, and to sort the returned DataFrame.

save

Save returned results locally with names “leaderboard_approx_mean.csv” and “leaderboard_approx_std.csv”

Returns:
pd.DataFrame

Averages in the same format as the input leaderboard. There is an additional column “Rank”.

pd.DataFrame

Standard errors in the same format as the input leaderboard. There is an additional column “Rank”.

Notes

The returned results are approximations of the precise leaderboard from get_leaderboard. Some metrics like RMSE may be different because data-point-wise and cross-validation-wise averaging are different.