R/model_evaluation.R

In vadmbertr/bonski.predict: Predict Where Ski Will Be Good

#' Evaluate different models
#'
#' @return data.frame. Result of the different models evaluation
#' @export
evaluate_models <- function() {
  na_replacements <- list("mean", "downup", "drop", FALSE)
  splits <- seq(.65, .8, .05)
  classify <- c(TRUE, FALSE)
  scorings <- list("neg_mean_absolute_error", NULL)
  ord_scores <- c(TRUE, FALSE)

  models <- list(MinirocketModel()) # leaves open handling of different models
  names(models) <- lapply(models, function(m) m$name)

  evaluations <- vector(mode = "list", length = length(models))
  names(evaluations) <- names(models)
  for (n in names(models)) {
    model <- models[[n]]
    tryCatch({
      evaluations[[n]] <- evaluate(model, na_replacements, splits, classify, scorings, ord_scores)
    },
    error = function(e) {
      message(paste0("Error with model: ", n))
      print(e)
    })
  }

  lapply(names(evaluations), function(name) dplyr::mutate(evaluations[[name]], name = name)) %>%
    data.table::rbindlist() %>%
    dplyr::relocate(name)
}