quollr (version 1.0.6)

gen_diffbin1_errors: Generate erros and MSE for different bin widths

Description

This function augments a dataset with predictions and error metrics obtained from a nonlinear dimension reduction (NLDR) model.

Usage

gen_diffbin1_errors(highd_data, nldr_data, hd_thresh = 1, bin1_vec = NULL)

Value

A tibble containing the augmented data with predictions, error metrics, and absolute error metrics.

Arguments

highd_data

A tibble that contains the high-dimensional data with a unique identifier.

nldr_data

A tibble that contains the embedding with a unique identifier.

hd_thresh

(default: 1) A numeric value using to filter high-density hexagons.

bin1_vec

A numeric vector contains the range of b1 values.

Examples

scurve_sample <- scurve |> head(100)
scurve_umap_sample <- scurve_umap |> head(100)
gen_diffbin1_errors(highd_data = scurve_sample, nldr_data = scurve_umap_sample)