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

r2 <- diff(range(s_curve_noise_umap$UMAP2))/diff(range(s_curve_noise_umap$UMAP1))
model <- fit_highd_model(training_data = s_curve_noise_training,
emb_df = s_curve_noise_umap_scaled, bin1 = 4, r2 = r2, col_start_highd = "x")
df_bin_centroids <- model$df_bin_centroids
df_bin <- model$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")
#> # A tibble: 1 × 2
#>   Error   MSE
#>   <dbl> <dbl>
#> 1  58.9 0.295