evalml.objectives.ExpVariance

class evalml.objectives.ExpVariance

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

evalml.objectives.MaxError.validate_inputs evalml.objectives.ExpVariance.__init__