recalibratePlpRefit: recalibratePlpRefit
In OHDSI/PatientLevelPrediction: Developing patient level prediction using data in the OMOP Common Data Model
View source: R/Recalibration.R
recalibratePlpRefit R Documentation
recalibratePlpRefit
Description
Train various models using a default parameter gird search or user specified parameters
Usage
recalibratePlpRefit(plpModel, newPopulation, newData)
Arguments
plpModel
The trained plpModel (runPlp$model)
newPopulation
The population created using createStudyPopulation() who will have their risks predicted
newData
An object of type plpData - the patient level prediction
data extracted from the CDM.
Details
The user can define the machine learning model to train (regularised logistic regression, random forest,
gradient boosting machine, neural network and )
Value
An object of class runPlp that is recalibrated on the new data
OHDSI/PatientLevelPrediction documentation built on April 27, 2024, 8:11 p.m.
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View source: R/Recalibration.R
| recalibratePlpRefit | R Documentation |
recalibratePlpRefit
Description
Train various models using a default parameter gird search or user specified parameters
Usage
recalibratePlpRefit(plpModel, newPopulation, newData)
Arguments
plpModel |
The trained plpModel (runPlp$model) |
newPopulation |
The population created using createStudyPopulation() who will have their risks predicted |
newData |
An object of type |
Details
The user can define the machine learning model to train (regularised logistic regression, random forest, gradient boosting machine, neural network and )
Value
An object of class runPlp that is recalibrated on the new data
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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