getThresholdSummary: Calculate all measures for sparse ROC

In OHDSI/PatientLevelPrediction: Develop Clinical Prediction Models Using the Common Data Model

Calculate all measures for sparse ROC

Description

Calculate all measures for sparse ROC

Usage

getThresholdSummary(
  prediction,
  predictionType = "binary",
  typeColumn = "evaluation"
)

Arguments

prediction	A prediction object
predictionType	The type of prediction (binary or survival)
typeColumn	A column that is used to stratify the results

Details

Calculates the TP, FP, TN, FN, TPR, FPR, accuracy, PPF, FOR and Fmeasure from a prediction object

Value

A data.frame with TP, FP, TN, FN, TPR, FPR, accuracy, PPF, FOR and Fmeasure

Examples

prediction <- data.frame(rowId = 1:100, 
                         outcomeCount = stats::rbinom(1:100, 1, prob=0.5),
                         value = runif(100), 
                         evaluation = rep("Train", 100))
summary <- getThresholdSummary(prediction)
str(summary)

OHDSI/PatientLevelPrediction documentation built on Feb. 14, 2025, 9:44 a.m.