Classification Workflows

Class Balance

Count Rare Labels

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.

minimum
class_balance.R
Replay: real traced execution (multi-file project)
minimum <- 2
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 <- 1
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 <- 3
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 = "")

  1. minimum ← 2

    1minimum <- 22label_name <- c("cat", "dog", "cat", "bird", "dog")
    values this step2minimum

  2. label_name ← cat, dog, cat, bird, dog

    1minimum <- 22label_name <- c("cat", "dog", "cat", "bird", "dog")3counts <- table(label_name)
    values this stepcat, dog, cat, bird, doglabel_name

  3. counts ← bird=1, cat=2, dog=2

    2label_name <- c("cat", "dog", "cat", "bird", "dog")3counts <- table(label_name)4rare <- names(counts[counts < minimum])
    values this stepbird=1, cat=2, dog=2counts5 labelslabel_name

  4. rare ← bird

    3counts <- table(label_name)4rare <- names(counts[counts < minimum])5rare_count <- length(rare)
    values this stepbirdrare2minimum

  5. rare_count ← 1

    4rare <- names(counts[counts < minimum])5rare_count <- length(rare)6label <- paste("rare", rare_count, sep = ":")
    values this step1rare_countbirdrare

  6. label ← rare:1

    5rare_count <- length(rare)6label <- paste("rare", rare_count, sep = ":")7cat(label, "\n", sep = "")
    values this steprare:1label1rare_count

  7. cat(label, " ", sep = "")

    6label <- paste("rare", rare_count, sep = ":")7cat(label, "\n", sep = "")
    outputrare:1
    values this steprare:1label

  1. minimum ← 1

    1minimum <- 12label_name <- c("cat", "dog", "cat", "bird", "dog")
    values this step1minimum

  2. label_name ← cat, dog, cat, bird, dog

    1minimum <- 12label_name <- c("cat", "dog", "cat", "bird", "dog")3counts <- table(label_name)
    values this stepcat, dog, cat, bird, doglabel_name

  3. counts ← bird=1, cat=2, dog=2

    2label_name <- c("cat", "dog", "cat", "bird", "dog")3counts <- table(label_name)4rare <- names(counts[counts < minimum])
    values this stepbird=1, cat=2, dog=2counts5 labelslabel_name

  4. rare ← none

    3counts <- table(label_name)4rare <- names(counts[counts < minimum])5rare_count <- length(rare)
    values this stepnonerare1minimum

  5. rare_count ← 0

    4rare <- names(counts[counts < minimum])5rare_count <- length(rare)6label <- paste("rare", rare_count, sep = ":")
    values this step0rare_countnonerare

  6. label ← rare:0

    5rare_count <- length(rare)6label <- paste("rare", rare_count, sep = ":")7cat(label, "\n", sep = "")
    values this steprare:0label0rare_count

  7. cat(label, " ", sep = "")

    6label <- paste("rare", rare_count, sep = ":")7cat(label, "\n", sep = "")
    outputrare:0
    values this steprare:0label

  1. minimum ← 3

    1minimum <- 32label_name <- c("cat", "dog", "cat", "bird", "dog")
    values this step3minimum

  2. label_name ← cat, dog, cat, bird, dog

    1minimum <- 32label_name <- c("cat", "dog", "cat", "bird", "dog")3counts <- table(label_name)
    values this stepcat, dog, cat, bird, doglabel_name

  3. counts ← bird=1, cat=2, dog=2

    2label_name <- c("cat", "dog", "cat", "bird", "dog")3counts <- table(label_name)4rare <- names(counts[counts < minimum])
    values this stepbird=1, cat=2, dog=2counts5 labelslabel_name

  4. rare ← bird, cat, dog

    3counts <- table(label_name)4rare <- names(counts[counts < minimum])5rare_count <- length(rare)
    values this stepbird, cat, dograre3minimum

  5. rare_count ← 3

    4rare <- names(counts[counts < minimum])5rare_count <- length(rare)6label <- paste("rare", rare_count, sep = ":")
    values this step3rare_count3 classesrare

  6. label ← rare:3

    5rare_count <- length(rare)6label <- paste("rare", rare_count, sep = ":")7cat(label, "\n", sep = "")
    values this steprare:3label3rare_count

  7. cat(label, " ", sep = "")

    6label <- paste("rare", rare_count, sep = ":")7cat(label, "\n", sep = "")
    outputrare:3
    values this steprare:3label
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.