This function extracts the specified table
Usage
getPredictionPerformanceTable(
connectionHandler,
schema,
plpTablePrefix = "plp_",
databaseTable = "database_meta_data",
table = "attrition",
modelDesignIds = NULL,
performanceIds = NULL,
evaluations = NULL
)Arguments
- connectionHandler
A connection handler that connects to the database and extracts sql queries. Create a connection handler via `ResultModelManager::ConnectionHandler$new()`.
- schema
The result database schema (e.g., 'main' for sqlite)
- plpTablePrefix
The prefix used for the patient level prediction results tables
- databaseTable
The name of the table with the database details (default 'database_meta_data')
- table
The table to extract (covariate_summary, attrition, prediction_distribution, threshold_summary, calibration_summary, evaluation_statistics or demographic_summary )
- modelDesignIds
(optional) restrict to the input modelDesignIds
- performanceIds
(optional) restrict to the input performanceIds
- evaluations
(optional) restrict to the type of evaluation (e.g., 'Test'/'Train'/'CV'/'Validation')
Details
Specify the connectionHandler, the resultDatabaseSettings, the table of interest and (optionally) a performanceId to filter to
See also
Other Prediction:
getFullPredictionPerformances(),
getPredictionAggregateTopPredictors(),
getPredictionCohorts(),
getPredictionCovariates(),
getPredictionDiagnosticTable(),
getPredictionDiagnostics(),
getPredictionHyperParamSearch(),
getPredictionIntercept(),
getPredictionLift(),
getPredictionModelDesigns(),
getPredictionOutcomes(),
getPredictionPerformances(),
getPredictionTargets(),
getPredictionTopPredictors()
Examples
conDet <- getExampleConnectionDetails()
connectionHandler <- ResultModelManager::ConnectionHandler$new(conDet)
#> Connecting using SQLite driver
attrition <- getPredictionPerformanceTable(
connectionHandler = connectionHandler,
schema = 'main',
table = 'attrition'
)