deepcave.utils.multi_objective_importance

# Multi-Objective importances

This module provides utilities for calculating multi-objective importances.

Functions

get_weightings(objectives_normed, df)	Calculate the weighting for the weighted importance using the points on the pareto-front.
is_pareto_efficient(costs)	Find the pareto-efficient points.

deepcave.utils.multi_objective_importance.get_weightings(objectives_normed, df)

Calculate the weighting for the weighted importance using the points on the pareto-front.

Parameters:

• objectives_normed (List[str]) – The normalized objective names as a list of strings.

• df (pandas.dataframe) – The dataframe containing the encoded data.

Returns:

weightings – The weightings.

Return type:

numpy.ndarray

deepcave.utils.multi_objective_importance.is_pareto_efficient(costs)

Find the pareto-efficient points.

Parameters:

costs (numpy.ndarray) – An (n_points, n_costs) array.

Returns:

is_efficient – A (n_points, ) boolean array, indicating whether each point is pareto-efficient.

Return type:

numpy.ndarray

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