run_rf_once.R

run_rf_once <- function(df, features, filenamestem, language="eng", ntree=500, mtry=5, training_percent=50) {
  
  feats <- features[which(df$language==language & df$genre!=""),]
  
  df <- get_subset(language=language, 
                   df=df)
  df.genres <- df$df.genres
  
  df.genres.sets <- get_training_and_testing_sets(features=feats, 
                                                  training_percent=training_percent, 
                                                  filenamestem=filenamestem, 
                                                  load=FALSE)
  
  features.training <- df.genres.sets$training
  features.testing <- df.genres.sets$testing
  
  features.training.split <- split_training_set(features=features.training, parts=5)
  features.split <- features.training.split
  

  aggr <- as.data.frame(matrix(nrow = 22, ncol = length(features)))
  names(aggr) <- append(names(features[names(features)!="is_poetry"]), "TOTAL")

  aggregated_results <- run_rf(features.split=features.split, 
                               filestem = paste0(filenamestem, "_"),
                               ntree=ntree, 
                               mtry=mtry)
  return(aggr)
}