Visualization (sklift.viz)¶
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sklift.viz.base.
plot_treatment_balance_curve
(uplift, treatment, random=True, winsize=0.1)[source]¶ Plot Treatment Balance curve.
Parameters: - uplift (1d array-like) – Predicted uplift, as returned by a model.
- treatment (1d array-like) – Treatment labels.
- random (bool, default True) – Draw a random curve.
- winsize (float, default 0.1) – Size of the sliding window to apply. Should be between 0 and 1, extremes excluded.
Returns: Object that stores computed values.
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sklift.viz.base.
plot_uplift_by_percentile
(y_true, uplift, treatment, strategy, kind='line', bins=10)[source]¶ Plot uplift score, treatment response rate and control response rate at each percentile.
Treatment response rate ia a target mean in the treatment group. Control response rate is a target mean in the control group. Uplift score is a difference between treatment response rate and control response rate.
Parameters: - 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.
'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.
- kind (string, ['line', 'bar']) –
The type of plot to draw. Default is ‘line’.
'line'
:- Generates a line plot.
'bar'
:- Generates a traditional bar-style plot.
- bins (int) – Determines а number of bins (and а relative percentile) in the test data. Default is 10.
Returns: Object that stores computed values.
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sklift.viz.base.
plot_uplift_preds
(trmnt_preds, ctrl_preds, log=False, bins=100)[source]¶ Plot histograms of treatment, control and uplift predictions.
Parameters: - trmnt_preds (1d array-like) – Predictions for all observations if they are treatment.
- ctrl_preds (1d array-like) – Predictions for all observations if they are control.
- log (bool, default False) – Logarithm of source samples.
- bins (integer or sequence, default 100) – Number of histogram bins to be used. If an integer is given, bins + 1 bin edges are calculated and returned. If bins is a sequence, gives bin edges, including left edge of first bin and right edge of last bin. In this case, bins is returned unmodified.
Returns: Object that stores computed values.
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sklift.viz.base.
plot_uplift_qini_curves
(y_true, uplift, treatment, random=True, perfect=False)[source]¶ Plot Uplift and Qini curves.
Parameters: - y_true (1d array-like) – Ground truth (correct) labels.
- uplift (1d array-like) – Predicted uplift, as returned by a model.
- treatment (1d array-like) – Treatment labels.
- random (bool, default True) – Draw a random curve.
- perfect (bool, default False) – Draw a perfect curve.
Returns: Object that stores computed values.