create_scoreSummary_list.R

create_scoreSummary_list <- function(container, classification_results) {
  labels <- c()
  probs <- c()
  
  for (name in colnames(classification_results)) {
    if(strsplit(name,"_")[[1]][2] == "LABEL") {
      labels <- as.data.frame(c(labels,classification_results[name]));
    } else {
      probs <- as.data.frame(c(probs,classification_results[name]));
    }
  }
  
  best_labels <- c()
  best_probs <- c()
  agree_scores <- c()
  unique <- sort(unique(container[2][[1]]))
  for (i in 1:nrow(classification_results)) {
    row_labels <- labels[i,]
    row_probs <- probs[i,]
    dist <- c()
    
    for (code in unique) dist <- append(dist,length(row_labels[row_labels==code]))
    
    if(length(colnames(probs)) > 1) {
      best_prob_name <- colnames(t(which.max(probs[i,])))[1]
      parse_prob_name <- strsplit(best_prob_name,"_")
      create_label_name <- paste(parse_prob_name[[1]][1],"_LABEL",sep="")
    } else {
      best_prob_name <- colnames(probs)
      parse_prob_name <- strsplit(best_prob_name,"_")
      create_label_name <- paste(parse_prob_name[[1]][1],"_LABEL",sep="")
    }
    
    agree_score <- as.vector(max(dist))
    best_label <- as.vector(unique[which.max(dist)])
    best_prob <- as.vector(classification_results[create_label_name][i,])
    
    if (agree_score == 1) best_label <- best_prob
    
    best_probs <- append(best_probs,best_prob)
    agree_scores <- append(agree_scores,agree_score)
    best_labels <- append(best_labels,best_label)
  }
  
  return(cbind(labels,BEST_LABEL=as.numeric(best_labels),BEST_PROB=best_probs, NUM_AGREE=agree_scores))
}