R/valid-metric.R

In andrewsommerlot/startml: Start doing machine learning with training optimization and ensembles of popular machine learning algorithms powered by scalable implementations in h2o

#' select_models
#'
# Gets validation metrics from a list of h2o models.
#'
#' @param model_list List object of H2O frames containing h2o model objects. No Default.
#' @param eval_metric Character object one of logloss, MSE, RMSE, MAE, AUC, or mean_per_class_error.
#' @return List object same length as model_list containing performance of each model on validation data with selected metric.
#' @export
valid_metric <- function(model_list, eval_metric) {
  if(eval_metric == "logloss") {
    metric <- lapply(model_list, h2o.logloss, valid = TRUE)
  } else if(eval_metric == "MSE") {
    metric <- lapply(model_list, h2o.mse, valid = TRUE)
  } else if(eval_metric == "RMSE") {
    metric <- lapply(model_list, h2o.rmse, valid = TRUE)
  } else if(eval_metric == "MAE") {
    metric <- lapply(model_list, h2o.mae, valid = TRUE)
  } else if(eval_metric == "AUC") {
    metric <- lapply(model_list, h2o.auc, valid = TRUE)
  } else if(eval_metric == "mean_per_class_error") {
    metric <- lapply(model_list, h2o.mean_per_class_error, valid = TRUE)
  }else if(eval_metric == "RMSLE") {
    metric <- lapply(model_list, h2o.rmsle, valid = TRUE)
  } else {
    stop("Choose an eval metric: logloss, MSE, RMSE, MAE, AUC, mean_per_class_error")
  }
  metric
}