Plot SVM decision boundary

Usage

tl_plot_svm_boundary(model, x_var = NULL, y_var = NULL, grid_size = 100, ...)

Arguments

model: A tidylearn SVM model object
x_var: Name of the x-axis variable. Defaults to the first numeric predictor in the model's formula.
y_var: Name of the y-axis variable. Defaults to the next numeric predictor in the model's formula.
grid_size: Number of points in each dimension for the grid (default: 100)
...: Additional arguments

Value

A ggplot object. The other predictors are held at their mean, or their most frequent level. A two-class model fitted with probabilities also gets the 0.5 probability contour.

Examples

# \donttest{
if (requireNamespace("e1071", quietly = TRUE)) {
  model <- tl_model(iris, Species ~ ., method = "svm")
  tl_plot_svm_boundary(model,
    x_var = "Sepal.Length", y_var = "Sepal.Width")
}

# }