AutoScore_fine_tuning {AutoScore}R Documentation

AutoScore STEP(iv): Fine-tune the score by revising cut_vec with domain knowledge (AutoScore Module 5)

Description

Domain knowledge is essential in guiding risk model development. For continuous variables, the variable transformation is a data-driven process (based on "quantile" or "kmeans" ). In this step, the automatically generated cutoff values for each continuous variable can be fine-tuned by combining, rounding, and adjusting according to the standard clinical norm. Revised cut_vec will be input with domain knowledge to update scoring table. User can choose any cut-off values/any number of categories. Then final Scoring table will be generated. Run vignette("Guide_book", package = "AutoScore") to see the guidebook or vignette.

Usage

AutoScore_fine_tuning(
  train_set,
  validation_set,
  final_variables,
  cut_vec,
  max_score = 100
)

Arguments

train_set

A processed data.frame that contains data to be analyzed, for training.

validation_set

A processed data.frame that contains data for validation purpose.

final_variables

A vector containing the list of selected variables, selected from Step(ii) AutoScore_parsimony. Run vignette("Guide_book", package = "AutoScore") to see the guidebook or vignette.

cut_vec

Generated from STEP(iii) AutoScore_weighting.Please follow the guidebook

max_score

Maximum total score (Default: 100).

Value

Generated final table of scoring model for downstream testing

References

See Also

AutoScore_rank, AutoScore_parsimony, AutoScore_weighting, AutoScore_testing,Run vignette("Guide_book", package = "AutoScore") to see the guidebook or vignette.

Examples

## Please see the guidebook or vignettes

[Package AutoScore version 0.2.0 Index]