Binary categories aren't handled correctly
Nobody has claimed this yet.
Assessment
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Newbie friendliness
- 45/100
- Issue type
- Bug
- Clarity
- Mostly clear
- Activity status
- Stale
- Tech stack
- r
- Domain
- data-visualization
Research direction
Locate the plot_area function and read its current handling of label/category levels. Check the binary-category behavior against the multinomial case described in the issue, then verify that both cases produce the expected plot; no specific test file is named.
Written by the indexing model from the issue text.
Description
When only two label/categories are present, this isn't handled correctly
One suggestion was to update the plot_area function as shown below.
if (length(levels(data[[y]])) > 2) {
# Multinomial case
predicted_probabilities <- Effect(x, mnom_model, xlevels = 300)
plot_data <- as.data.frame(predicted_probabilities)
} else {
# Binary case - still using multinom for consistency
new_data <- data.frame(x = seq(min(data[[x]]), max(data[[x]]), length.out = 300))
predicted_probabilities <- predict(mnom_model, newdata = new_data, type = "probs")
- Dominant language
- R
- Stars
- 1
- Forks
- 1
- PR merge metrics
- No merged PRs in 30d
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