augment: Augment Data with Predictions and Error Metrics

In quollr: Visualising How Nonlinear Dimension Reduction Warps Your Data

Augment Data with Predictions and Error Metrics

Description

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

Usage

augment(highd_data, model_2d, model_highd)

Arguments

highd_data	The dataset containing high-dimensional coordinates and an unique identifier.
model_2d	Centroid coordinates of hexagonal bins in 2-D space.
model_highd	Centroid coordinates of hexagonal bins in high dimensions.

Value

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

Examples

augment(highd_data = scurve, model_highd = scurve_model_obj$model_highd,
model_2d = scurve_model_obj$model_2d)

quollr documentation built on Aug. 8, 2025, 6:08 p.m.