evalml.objectives.CostBenefitMatrix

class evalml.objectives.CostBenefitMatrix(true_positive, true_negative, false_positive, false_negative)

Score using a cost-benefit matrix. Scores quantify the benefits of a given value, so greater numeric scores represents a better score. Costs and scores can be negative, indicating that a value is not beneficial. For example, in the case of monetary profit, a negative cost and/or score represents loss of cash flow.

name = 'Cost Benefit Matrix'

greater_is_better = True

perfect_score = inf

positive_only = False

problem_types = [<ProblemTypes.BINARY: 'binary'>, <ProblemTypes.TIME_SERIES_BINARY: 'time series binary'>]

score_needs_proba = False

Methods

__init__	Create instance of CostBenefitMatrix.
calculate_percent_difference	Calculate the percent difference between scores.
decision_function	Apply a learned threshold to predicted probabilities to get predicted classes.
is_defined_for_problem_type
objective_function	Calculates cost-benefit of the using the predicted and true values.
optimize_threshold	Learn a binary classification threshold which optimizes the current objective.
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.LeadScoring.validate_inputs evalml.objectives.CostBenefitMatrix.__init__