gen_summary {quollr}

Generate evaluation metrics

Description

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

Usage

gen_summary(test_data, prediction_df, df_bin, col_start = "x")

Arguments

test_data

The data set containing high-dimensional data along with an unique identifier.

prediction_df

The data set with 2D embeddings, IDs, and predicted hexagonal IDs.

df_bin

The data set with averaged/weighted high-dimensional data.

col_start

The text that begin the column name of the high-dimensional data.

Value

A list contains MSE and AIC values.

Examples

model <- fit_highd_model(training_data = s_curve_noise_training, x = "UMAP1", y = "UMAP2",
nldr_df_with_id = s_curve_noise_umap_scaled, col_start_2d = "UMAP", col_start_highd = "x")
df_bin_centroids <- model$df_bin_centroids
df_bin <- model$df_bin
pred_emb_list <- predict_emb(test_data = s_curve_noise_training,
df_bin_centroids = df_bin_centroids, df_bin = df_bin, type_NLDR = "UMAP")
pred_df_test <- as.data.frame(do.call(cbind, pred_emb_list))
gen_summary(test_data = s_curve_noise_training, prediction_df = pred_df_test,
df_bin = df_bin, col_start = "x")