Explore high-dimensional classification boundaries

Generates a high-dimensional uniform domain and identifies points near the decision boundaries of multiple models.

Usage

boundary_explore_nd(models, data, n_points = 10000, threshold = 0.05)

Arguments

models

A named list of fitted classbound model objects.

data

A data frame representing the original training data. The bounding box of this data determines the simulation domain.

n_points

Integer. Number of points to simulate in the high-dimensional space (default: 10000).

threshold

Numeric. A percentile threshold (0 to 1) for determining boundary proximity. Points below this advantage percentile are considered boundary-near. Default: 0.05.

Value

A data frame containing the simulated coordinates, the predicted classes for each model (prefixed with Y_), and a logical is_boundary column indicating if the point is near the boundary for ANY of the provided models.