scikitplot.snsx#

Seaborn-style scikit-plots Plotting.

User guide. See the snsx Seaborn eXtended (experimental) section for further details.

.api.metrics to SeabornX#

aucplot

AUC curve plot, Seaborn-style.

evalplot

Visualization of the Confusion Matrix [R039b9d226f6e-1] alongside a text report showing key classification metrics.

.kds to SeabornX#

Decile-based [2] model evaluation module (Lift, Gains, KS statistics).

The _decile module includes plots for machine learning evaluation decile analysis e.g. Gain, Lift and Decile charts, etc.

In descriptive statistics, a decile is any of the nine values that divide the sorted data into ten equal parts, so that each part represents 1/10 of the sample or population. A decile is one possible form of a quantile; others include the quartile and percentile. A decile rank arranges the data in order from lowest to highest and is done on a scale of one to ten where each successive number corresponds to an increase of 10 percentage points. See [2] for model details.

References

User guide. See the decile-index section for further details.

decileplot

Given binary labels y_true (0/1) and probabilities y_score 1d array, compute/plot a decile [R9ce98ddf8b9b-2] table.

print_labels

Pretty-print the legend of decile table column names.