report#

scikitplot.decile.kds.report(y_true, y_score, *, pos_label=None, class_index=1, feature_infos=True, digits=3, title_fontsize='large', text_fontsize='medium', plot_style=None, figsize=(10, 5), nrows=2, ncols=2, data=None, **kwargs)[source]#

Generate a decile table and four plots.

from labels and probabilities.

Parameters:
y_truearray-like, shape (n_samples,)

Ground truth (correct) target values.

y_scorearray-like, shape (n_samples, n_classes)

Prediction probabilities for each class returned by a classifier.

class_indexint, optional, default=1

Index of the class of interest for multi-class classification. Ignored for binary classification.

labelsbool, optional, default=True

If True, prints a legend for the abbreviations of decile table column names.

Deprecated since version 0.3.9: This parameter is deprecated and will be removed in version 0.5.0. Use feature_infos instead.

feature_infosbool, optional, default=True

If True, prints a legend for the abbreviations of decile table column names.

Added in version 0.3.9.

title_fontsizestr or int, optional, default=’large’

Font size for the plot title. Use e.g., “small”, “medium”, “large” or integer-values.

text_fontsizestr or int, optional, default=’medium’

Font size for the text in the plot. Use e.g., “small”, “medium”, “large” or integer-values.

digitsint, optional, default=3

Number of digits for formatting output floating point values. Use e.g., 2 or 4.

Added in version 0.3.9.

**kwargsdict, optional

Generic keyword arguments.

Returns:
pandas.DataFrame

The dataframe containing the decile table with the deciles and related information.

Other Parameters:
axmatplotlib.axes.Axes, optional, default=None

The axis to plot the figure on. If None is passed in the current axes will be used (or generated if required).

Added in version 0.4.0.

figmatplotlib.pyplot.figure, optional, default: None

The figure to plot the Visualizer on. If None is passed in the current plot will be used (or generated if required).

Added in version 0.4.0.

figsizetuple, optional, default=None

Width, height in inches. Tuple denoting figure size of the plot e.g. (12, 5)

Added in version 0.4.0.

nrowsint, optional, default=1

Number of rows in the subplot grid.

Added in version 0.4.0.

ncolsint, optional, default=1

Number of columns in the subplot grid.

Added in version 0.4.0.

plot_stylestr, optional, default=None

Check available styles with “plt.style.available”. Examples include: [‘ggplot’, ‘seaborn’, ‘bmh’, ‘classic’, ‘dark_background’, ‘fivethirtyeight’, ‘grayscale’, ‘seaborn-bright’, ‘seaborn-colorblind’, ‘seaborn-dark’, ‘seaborn-dark-palette’, ‘tableau-colorblind10’, ‘fast’].

Added in version 0.4.0.

show_figbool, default=True

Show the plot.

Added in version 0.4.0.

save_figbool, default=False

Save the plot. Used by save_plot_decorator.

Added in version 0.4.0.

save_fig_filenamestr, optional, default=’’

Specify the path and filetype to save the plot. If nothing specified, the plot will be saved as png inside result_images under to the current working directory. Defaults to plot image named to used func.__name__. Used by save_plot_decorator.

Added in version 0.4.0.

overwritebool, optional, default=True

If False and a file exists, auto-increments the filename to avoid overwriting.

Added in version 0.4.0.

add_timestampbool, optional, default=False

Whether to append a timestamp to the filename. Default is False.

Added in version 0.4.0.

verbosebool, optional

If True, enables verbose output with informative messages during execution. Useful for debugging or understanding internal operations such as backend selection, font loading, and file saving status. If False, runs silently unless errors occur.

Default is False.

Added in version 0.4.0: The verbose parameter was added to control logging and user feedback verbosity.

See also

print_labels

A legend for the abbreviations of decile table column names.

decile_table

Generates the Decile Table from labels and probabilities.

plot_lift

Generates the Decile based cumulative Lift Plot from labels and probabilities.

plot_lift_decile_wise

Generates the Decile-wise Lift Plot from labels and probabilities.

plot_cumulative_gain

Generates the cumulative Gain Plot from labels and probabilities.

plot_ks_statistic

Generates the Kolmogorov-Smirnov (KS) Statistic Plot from labels and probabilities.

References

[1] tensorbored/kds

Examples

>>> from sklearn.datasets import (
...     load_breast_cancer as data_2_classes,
... )
>>> from sklearn.model_selection import train_test_split
>>> from sklearn.tree import DecisionTreeClassifier
...
>>> X, y = data_2_classes(return_X_y=True, as_frame=True)
>>> X_train, X_test, y_train, y_test = train_test_split(
...     X, y, test_size=0.5, random_state=0
... )
>>> clf = DecisionTreeClassifier(max_depth=1, random_state=0).fit(
...     X_train, y_train
... )
>>> y_prob = clf.predict_proba(X_test)
...
>>> import scikitplot.decile.kds as kds
>>> dt = kds.report(
>>>     y_test, y_prob, class_index=1
>>> )
>>> dt

LABELS INFO:

 prob_min         : Minimum probability in a particular decile
 prob_max         : Minimum probability in a particular decile
 prob_avg         : Average probability in a particular decile
 cnt_events       : Count of events in a particular decile
 cnt_resp         : Count of responders in a particular decile
 cnt_non_resp     : Count of non-responders in a particular decile
 cnt_resp_rndm    : Count of responders if events assigned randomly in a particular decile
 cnt_resp_wiz     : Count of best possible responders in a particular decile
 resp_rate        : Response Rate in a particular decile [(cnt_resp/cnt_cust)*100]
 cum_events       : Cumulative sum of events decile-wise 
 cum_resp         : Cumulative sum of responders decile-wise 
 cum_resp_wiz     : Cumulative sum of best possible responders decile-wise 
 cum_non_resp     : Cumulative sum of non-responders decile-wise 
 cum_events_pct   : Cumulative sum of percentages of events decile-wise 
 cum_resp_pct     : Cumulative sum of percentages of responders decile-wise 
 cum_resp_pct_wiz : Cumulative sum of percentages of best possible responders decile-wise 
 cum_non_resp_pct : Cumulative sum of percentages of non-responders decile-wise 
 KS               : KS Statistic decile-wise 
 lift             : Cumuative Lift Value decile-wise
../../_images/scikitplot.decile.kds.report_0_1.png
decile prob_min prob_max prob_avg cnt_cust cnt_resp cnt_non_resp cnt_resp_rndm cnt_resp_wiz resp_rate cum_cust cum_resp cum_resp_wiz cum_non_resp cum_cust_pct cum_resp_pct cum_resp_pct_wiz cum_non_resp_pct KS lift
0 1 0.923077 0.923077 0.923077 29.0 29.0 0.0 18.4 29 100.000000 29.0 29.0 29 0.0 10.175439 15.760870 15.760870 0.000000 15.760870 1.548913
1 2 0.923077 0.923077 0.923077 28.0 25.0 3.0 18.4 28 89.285714 57.0 54.0 57 3.0 20.000000 29.347826 30.978261 2.970297 26.377529 1.467391
2 3 0.923077 0.923077 0.923077 29.0 26.0 3.0 18.4 29 89.655172 86.0 80.0 86 6.0 30.175439 43.478261 46.739130 5.940594 37.537667 1.440849
3 4 0.923077 0.923077 0.923077 28.0 24.0 4.0 18.4 28 85.714286 114.0 104.0 114 10.0 40.000000 56.521739 61.956522 9.900990 46.620749 1.413043
4 5 0.923077 0.923077 0.923077 29.0 28.0 1.0 18.4 29 96.551724 143.0 132.0 143 11.0 50.175439 71.739130 77.717391 10.891089 60.848041 1.429766
5 6 0.923077 0.923077 0.923077 28.0 26.0 2.0 18.4 28 92.857143 171.0 158.0 171 13.0 60.000000 85.869565 92.934783 12.871287 72.998278 1.431159
6 7 0.049020 0.923077 0.832657 29.0 19.0 10.0 18.4 13 65.517241 200.0 177.0 184 23.0 70.175439 96.195652 100.000000 22.772277 73.423375 1.370788
7 8 0.049020 0.049020 0.049020 28.0 6.0 22.0 18.4 0 21.428571 228.0 183.0 184 45.0 80.000000 99.456522 100.000000 44.554455 54.902067 1.243207
8 9 0.049020 0.049020 0.049020 29.0 1.0 28.0 18.4 0 3.448276 257.0 184.0 184 73.0 90.175439 100.000000 100.000000 72.277228 27.722772 1.108949
9 10 0.049020 0.049020 0.049020 28.0 0.0 28.0 18.4 0 0.000000 285.0 184.0 184 101.0 100.000000 100.000000 100.000000 100.000000 0.000000 1.000000
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