Generate evaluation metrics — glance • quollr

This function generates an evaluation data frame based on the provided data and predictions.

Usage

glance(
  df_bin_centroids,
  df_bin,
  training_data,
  newdata = NULL,
  type_NLDR,
  col_start = "x"
)

Arguments

df_bin_centroids: Centroid coordinates of hexagonal bins in 2D space.
df_bin: Centroid coordinates of hexagonal bins in high dimensions.
training_data: Training data used to fit the model.
newdata: Data to be augmented with predictions and error metrics. If NULL, the training data is used (default is NULL).
type_NLDR: The type of non-linear dimensionality reduction (NLDR) used.
col_start: The text that begin the column name of the high-dimensional data.

Value

A tibble contains Error, and MSE values.

Examples

df_bin_centroids <- s_curve_obj$s_curve_umap_model_distance_df$df_bin_centroids
#> Warning: Unknown or uninitialised column: `df_bin_centroids`.
df_bin <- s_curve_obj$s_curve_umap_model_distance_df$df_bin
#> Warning: Unknown or uninitialised column: `df_bin`.
glance(df_bin_centroids = df_bin_centroids, df_bin = df_bin,
training_data = s_curve_noise_training, newdata = NULL, type_NLDR = "UMAP",
col_start = "x")
#> Error in names(df_bin) <- `*vtmp*`: attempt to set an attribute on NULL