plotLearningCurve: plotLearningCurve

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

plotLearningCurve

Description

Create a plot of the learning curve using the object returned from createLearningCurve.

Usage

plotLearningCurve(
  learningCurve,
  metric = "AUROC",
  abscissa = "events",
  plotTitle = "Learning Curve",
  plotSubtitle = NULL,
  fileName = NULL
)

Arguments

learningCurve	An object returned by createLearningCurve function.
metric	Specifies the metric to be plotted: 'AUROC' - use the area under the Receiver Operating Characteristic curve 'AUPRC' - use the area under the Precision-Recall curve 'sBrier' - use the scaled Brier score
abscissa	Specify the abscissa metric to be plotted: 'events' - use number of events 'observations' - use number of observations
plotTitle	Title of the learning curve plot.
plotSubtitle	Subtitle of the learning curve plot.
fileName	Filename of plot to be saved, for example 'plot.png'. See the function ggsave in the ggplot2 package for supported file formats.

Value

A ggplot object. Use the ggsave function to save to file in a different format.

Examples

 
data("simulationProfile")
plpData <- simulatePlpData(simulationProfile, n = 1000)
outcomeId <- 3
modelSettings <- setLassoLogisticRegression(seed=42)
learningCurve <- createLearningCurve(plpData, outcomeId, modelSettings = modelSettings,
saveDirectory = file.path(tempdir(), "learningCurve"), cores = 2)
plotLearningCurve(learningCurve)

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