R/model_xgboost.R

In PaoloBnn/Retip: Retention Time Prediction for Metabolomics

#' Build XGboost Model
#' @export fit.xgboost
#' @param x A training dataset with calculated Chemical Descriptors
#' @return  Returns a trained model ready to predict
#' @examples
#' \donttest{
#' xgb <- fit.xgboost(training)}


fit.xgboost <- function(x) {

  # set up train control for 10 times cross validation
  cv.ctrl <- caret::trainControl(method = "cv", number = 10)

  # These are the tune grid parameters
  xgb.grid <- base::expand.grid(nrounds = c(300, 400, 500, 600,
                                            700, 800, 1000),
                                max_depth = c(2, 3, 4, 5),
                                eta = c(0.01, 0.02),
                                gamma = c(1),
                                colsample_bytree = c(0.5),
                                subsample = c(0.5),
                                min_child_weight = c(10))

  print("Computing model Xgboost  ... Please wait ...")

  # Model training using the above parameters
  set.seed(101)
  model_xgb <- caret::train(RT ~ .,
                            data = x,
                            method = "xgbTree",
                            metric = "RMSE",
                            trControl = cv.ctrl,
                            tuneGrid = xgb.grid)

  print("End training")

  return(model_xgb)
}