explorapp: Shiny app to visually explore and compare classification...

In classbound: Visualization for Classification Decision Boundaries

Shiny app to visually explore and compare classification boundaries for built-in, custom, and tidymodels algorithms in 2D

Description

Shiny app to visually explore and compare classification boundaries for built-in, custom, and tidymodels algorithms in 2D

Usage

explorapp(data = NULL, target_col = NULL, custom_models = list())

Arguments

data	Optional data frame to import directly into the app.
target_col	Optional string specifying the column in data that contains the true class labels.
custom_models	A list of custom models to inject into the app's comparison UI. Each element should be a named list containing at least fn (the model fitting function). Optionally, it can contain args (a list of arguments to pass to fn) and predict_args (a function returning a list of arguments for prediction).

Value

No return value, called for side effects. Shinyapp is launched.

Examples

if (interactive()) {
  # Launch with default models
  explorapp()

  # Launch with a custom SVM model
  explorapp(custom_models = list(
    "SVM" = list(
      fn = e1071::svm,
      args = list(kernel = "linear")
    )
  ))
}

classbound documentation built on Sept. 30, 2026, 5:13 p.m.