Class balance checks show whether each label has enough examples to learn from.

Program

Play the script to change the minimum class size and count rare labels.

class_balance.R
minimum <- 
label_name <- c("cat", "dog", "cat", "bird", "dog")
counts <- table(label_name)
rare <- names(counts[counts < minimum])
rare_count <- length(rare)
label <- paste("rare", rare_count, sep = ":")
cat(label, "\n", sep = "")
minimum <- 
label_name <- c("cat", "dog", "cat", "bird", "dog")
counts <- table(label_name)
rare <- names(counts[counts < minimum])
rare_count <- length(rare)
label <- paste("rare", rare_count, sep = ":")
cat(label, "\n", sep = "")
minimum <- 
label_name <- c("cat", "dog", "cat", "bird", "dog")
counts <- table(label_name)
rare <- names(counts[counts < minimum])
rare_count <- length(rare)
label <- paste("rare", rare_count, sep = ":")
cat(label, "\n", sep = "")
class count `table(label_name)` counts examples per class.
rare class `counts < minimum` marks classes below the selected minimum.
balance check A rare-class count warns when training data is thin.