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Extract the top N predictors across a set of models

Source: R/PredictionQueries.R
getPredictionAggregateTopPredictors.Rd

This function extracts the top N predictors across models by finding the sum of the absolute coefficient value across models.

Usage

getPredictionAggregateTopPredictors(
  connectionHandler,
  schema,
  plpTablePrefix = "plp_",
  cgTablePrefix = "cg_",
  databaseTable = "database_meta_data",
  modelDesignIds = 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

cgTablePrefix

The prefix used for the cohort generator results tables

databaseTable

The name of the table with the database details (default 'database_meta_data')

modelDesignIds

One or more model design IDs to restrict to

Value

Returns a data.frame with the columns:

  • databaseName the name of the database the model was developed on

  • tarStartDay the time-at-risk start day

  • tarStartAnchor whether the time-at-risk start is relative to cohort start or end

  • tarEndDay the time-at-risk end day

  • tarEndAnchor whether the time-at-risk end is relative to cohort start or end

  • covariateId the FeatureExtraction covariate identifier

  • covariateName the name of the covariate

  • conceptId the covariates corresponding concept or 0

  • sumCovariateValue the total absolute feature importance or coefficient value

  • numberOfTimesPredictive number of models that contained the covariate

Details

Specify the connectionHandler, the resultDatabaseSettings and (optionally) any modelDesignIds to restrict to

See also

Other Prediction: getFullPredictionPerformances(), getPredictionCohorts(), getPredictionCovariates(), getPredictionDiagnosticTable(), getPredictionDiagnostics(), getPredictionHyperParamSearch(), getPredictionIntercept(), getPredictionLift(), getPredictionModelDesigns(), getPredictionOutcomes(), getPredictionPerformanceTable(), getPredictionPerformances(), getPredictionTargets(), getPredictionTopPredictors()

Examples

conDet <- getExampleConnectionDetails()

connectionHandler <- ResultModelManager::ConnectionHandler$new(conDet)
#> Connecting using SQLite driver

topPreds <- getPredictionAggregateTopPredictors(
  connectionHandler = connectionHandler, 
  schema = 'main',
  modelDesignIds = c(1,2,5)
)