FraudCost(retry_percentage=0.5, interchange_fee=0.02, fraud_payout_percentage=1.0, amount_col='amount')¶
Score the percentage of money lost of the total transaction amount process due to fraud.
name= 'Fraud Cost'¶
problem_types= [<ProblemTypes.BINARY: 'binary'>, <ProblemTypes.TIME_SERIES_BINARY: 'time series binary'>]¶
Create instance of FraudCost
Calculate the percent difference between scores.
Determine if a transaction is fraud given predicted probabilities, threshold, and dataframe with transaction amount.
Calculate amount lost to fraud per transaction given predictions, true values, and dataframe with transaction amount.
Learn a binary classification threshold which optimizes the current objective.
Returns a numerical score indicating performance based on the differences between the predicted and actual values.
Validates the input based on a few simple checks.