list of lists where each list is renamed as the data partitions source and returns the
following components:
source. Character: data partitions for which ROC curve data is returned
(see DataPartition).
negativeClassPredictions. Numeric: example predictions for the negative class for each
data partition source.
rocPoints. data.frame: each row represents pre-calculated metrics (accuracy, f1_score,
false_negative_score, true_negative_score, true_positive_score, false_positive_score,
true_negative_rate, false_positive_rate, true_positive_rate, matthews_correlation_coefficient,
positive_predictive_value, negative_predictive_value, threshold) associated with different
thresholds for the ROC curve.
positiveClassPredictions. Numeric: example predictions for the positive class for each
data partition source.
Arguments
model
dataRobotModel. A DataRobot model object like that returned by GetModel.
fallbackToParentInsights
logical. If TRUE, this will return the lift chart data for the
model's parent if the lift chart is not available for the model and the model has a parent
model.