sklift.metrics.metrics.uplift_by_percentile(y_true, uplift, treatment, strategy='overall', bins=10, std=False, total=False, string_percentiles=True)[source]

Compute metrics: uplift, group size, group response rate, standard deviation at each percentile.

Metrics in columns and percentiles in rows of pandas DataFrame:

  • n_treatment, n_control - group sizes.

  • response_rate_treatment, response_rate_control - group response rates.

  • uplift - treatment response rate substract control response rate.

  • std_treatment, std_control - (optional) response rates standard deviation.

  • std_uplift - (optional) uplift standard deviation.

  • y_true (1d array-like) – Correct (true) target values.

  • uplift (1d array-like) – Predicted uplift, as returned by a model.

  • treatment (1d array-like) – Treatment labels.

  • strategy (string, ['overall', 'by_group']) –

    Determines the calculating strategy. Default is ‘overall’.

    • 'overall':

      The first step is taking the first k observations of all test data ordered by uplift prediction (overall both groups - control and treatment) and conversions in treatment and control groups calculated only on them. Then the difference between these conversions is calculated.

    • 'by_group':

      Separately calculates conversions in top k observations in each group (control and treatment) sorted by uplift predictions. Then the difference between these conversions is calculated

  • std (bool) – If True, add columns with the uplift standard deviation and the response rate standard deviation. Default is False.

  • total (bool) – If True, add the last row with the total values. Default is False. The total uplift computes as a total response rate treatment - a total response rate control. The total response rate is a response rate on the full data amount.

  • bins (int) – Determines the number of bins (and the relative percentile) in the data. Default is 10.

  • string_percentiles (bool) – type of percentiles in the index: float or string. Default is True (string).


DataFrame where metrics are by columns and percentiles are by rows.

Return type