LeadScoring(true_positives=1, false_positives=- 1)¶
name= 'Lead Scoring'¶
problem_types= [<ProblemTypes.BINARY: 'binary'>, <ProblemTypes.TIME_SERIES_BINARY: 'time series binary'>]¶
Calculate the percent difference between scores.
Apply a learned threshold to predicted probabilities to get predicted classes.
Calculate the profit per lead.
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.