datarobot (version 2.18.6)

GetRocCurve: Retrieve ROC curve data for a model for a particular data partition (see DataPartition)

Description

Retrieve ROC curve data for a model for a particular data partition (see DataPartition)

Usage

GetRocCurve(
  model,
  source = DataPartition$VALIDATION,
  fallbackToParentInsights = FALSE
)

Value

list with the following components:

• source. Character: data partition for which ROC curve data is returned (see DataPartition).

• negativeClassPredictions. Numeric: example predictions for the negative class.

• 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.

Arguments

model

dataRobotModel. A DataRobot model object like that returned by GetModel.

source

character. The data partition for which data would be returned. Default is DataPartition$VALIDATION. See DataPartition for details.

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.

Examples

if (FALSE) {
  projectId <- "59a5af20c80891534e3c2bde"
  modelId <- "5996f820af07fc605e81ead4"
  model <- GetModel(projectId, modelId)
  GetRocCurve(model)
}