scikitplot.utils

This package/module is designed to be compatible with both Python 2 and Python 3. The imports below ensure consistent behavior across different Python versions by enforcing Python 3-like behavior in Python 2.

Utility functions and helpers for the scikitplot library.

Developer guide. See the Utilities for Developers section for further details.

Optimal mathematical operations

This package/module is designed to be compatible with both Python 2 and Python 3. The imports below ensure consistent behavior across different Python versions by enforcing Python 3-like behavior in Python 2.

Helper functions and generic utilities for use in scikitplot code.

helpers.combine_and_save_figures	Combine multiple figures into a single image, save it (if specified), and return the combined figure.
helpers.validate_labels	Validates the labels passed into arguments such as true_labels or pred_labels in functions like plot_confusion_matrix.
helpers.cumulative_gain_curve	Generate the data points necessary to plot the Cumulative Gain curve for binary classification tasks.
helpers.binary_ks_curve	Generate the data points necessary to plot the Kolmogorov-Smirnov (KS) curve for binary classification tasks.
helpers.sigmoid	Compute the sigmoid function for the input array x.
helpers.softmax	Compute the softmax function for each row of the input array x.