R/createThoraricSurgery.R

In jkrijthe/createdatasets: Download and preprocess common benchmark dataset for use in reproduceable simulation studies

#' Create Thoraric Surgery dataset
#' 
#' From UCI:
#' 1. DGN: Diagnosis - specific combination of ICD-10 codes for primary and secondary as well multiple tumours if any (DGN3,DGN2,DGN4,DGN6,DGN5,DGN8,DGN1) 
#' 2. PRE4: Forced vital capacity - FVC (numeric) 
#' 3. PRE5: Volume that has been exhaled at the end of the first second of forced expiration - FEV1 (numeric) 
#' 4. PRE6: Performance status - Zubrod scale (PRZ2,PRZ1,PRZ0) 
#' 5. PRE7: Pain before surgery (T,F) 
#' 6. PRE8: Haemoptysis before surgery (T,F) 
#' 7. PRE9: Dyspnoea before surgery (T,F) 
#' 8. PRE10: Cough before surgery (T,F) 
#' 9. PRE11: Weakness before surgery (T,F) 
#' 10. PRE14: T in clinical TNM - size of the original tumour, from OC11 (smallest) to OC14 (largest) (OC11,OC14,OC12,OC13) 
#' 11. PRE17: Type 2 DM - diabetes mellitus (T,F) 
#' 12. PRE19: MI up to 6 months (T,F) 
#' 13. PRE25: PAD - peripheral arterial diseases (T,F) 
#' 14. PRE30: Smoking (T,F) 
#' 15. PRE32: Asthma (T,F) 
#' 16. AGE: Age at surgery (numeric) 
#' 17. Risk1Y: 1 year survival period - (T)rue value if died (T,F) 
#' 
#' Task: formula(Risk1Yr ~ .)
#' 
#' @references Zieba, M., Tomczak, J. M., Lubicz, M., & {'S}wi{k{a}}tek J. (2013). Boosted SVM for extracting rules from imbalanced data in application to prediction of the post-operative life expectancy in the lung cancer patients. Applied Soft Computing.
#'  
#' @inheritParams createDiabetes
#' @return The dataset as a \code{\link[data.table]{data.table}}
#' @seealso \url{https://archive.ics.uci.edu/ml/datasets/Thoracic+Surgery+Data}
#' @export
createThoraricSurgery<-function(file=getfilepath("thoraricsurgery.rds"),write=TRUE,read=TRUE) {
  # Check if the user forced the recreation of the datasets or whether the datafile is missing on disk
  if (!read | !file.exists(file)) {
    requireNamespace("foreign")
    data <- data.table(read.arff("http://archive.ics.uci.edu/ml/machine-learning-databases/00277/ThoraricSurgery.arff"))
    
    
    if (write) {
      saveRDS(data, file=file)
    }
  } else {
    data<-readRDS(file)
  }
  
  return(data)
}