Generate evaluation metrics for a hex_model object — glance.highd_vis

This function computes evaluation metrics (Error and RMSE) by comparing the high-dimensional data to the predictions obtained from a hex_model object.

Usage

# S3 method for class 'highd_vis_model'
glance(model_object, highd_data, ...)

Arguments

model_object: An object of class hex_model generated by fit_highd_model().
highd_data: A data frame or tibble containing the original high-dimensional data with an ID column.
...: Additional arguments (currently unused).

Value

A tibble contains Error, and MSE values.

Examples

# Assuming 'fit' is a hex_model object and 'scurve' contains the original data:
fit <- fit_highd_model(highd_data = scurve, nldr_data = scurve_umap, b1 = 30,
q = 0.1, hd_thresh = 5)
#> Warning: triangle collapsed!
#> Warning: three points coincide or are collinear!
#> ✔ Model generated successfully!!!
glance(fit, highd_data = scurve)
#> # A tibble: 1 × 2
#>   Error  RMSE
#>   <dbl> <dbl>
#> 1 1472.  1.05