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quollr (version 0.3.7)

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, benchmark_highdens = 1)

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.

benchmark_highdens

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

Examples

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

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