pyjedai.visualization

Functions

create_confusion_matrix(confusion_matrix, title)
plot_attribute_group_avg_ranking(...[, dfs, ...])	For each unique combination of given attributes calculates its average feature value across datasets for each budget.
plot_attribute_group_avg_top_distance(...[, ...])	For each unique combination of given attributes calculates its feature's value average difference from the best value across datasets for each budget.
plot_attributes_performance_for_budget(...)	For each unique combination of given attributes calculates its feature value's average distance from best / ranking per budget.
plot_feature_progress_per_attribute_group(...)	Plots the progress of the value of requested feature per budget for experiments grouped by the attributes.