sklift.metrics.response_rate_by_percentile
- sklift.metrics.metrics.response_rate_by_percentile(y_true, uplift, treatment, group, strategy='overall', bins=10)[source]
Compute response rate (target mean in the control or treatment group) at each percentile.
- Parameters
y_true (1d array-like) – Correct (true) binary target values.
uplift (1d array-like) – Predicted uplift, as returned by a model.
treatment (1d array-like) – Treatment labels.
group (string, ['treatment', 'control']) –
Group type for computing response rate: treatment or control.
'treatment'
:Values equal 1 in the treatment column.
'control'
:Values equal 0 in the treatment column.
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.
bins (int) – Determines the number of bins (and relative percentile) in the data. Default is 10.
- Returns
response rate at each percentile for control or treatment group, variance of the response rate at each percentile, group size at each percentile.
- Return type
array (shape = [>2]), array (shape = [>2]), array (shape = [>2])