evalml.objectives.ExpVariance

class evalml.objectives.ExpVariance[source]

Explained variance score for regression.

name = 'ExpVariance'
greater_is_better = True
perfect_score = 1.0
positive_only = False
problem_types = [<ProblemTypes.REGRESSION: 'regression'>, <ProblemTypes.TIME_SERIES_REGRESSION: 'time series regression'>]
score_needs_proba = False

Methods

__init__

Initialize self.

calculate_percent_difference

Calculate the percent difference between scores.

is_defined_for_problem_type

objective_function

Computes the relative value of the provided predictions compared to the actual labels, according a specified metric

score

Returns a numerical score indicating performance based on the differences between the predicted and actual values.

validate_inputs

Validates the input based on a few simple checks.

Class Inheritance

Inheritance diagram of ExpVariance