augment

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

To construct a model in 2-D space from 2-D nonlinear
dimension reduction data and then lift it to the high-dimensional
space. Additionally, provides tools to visualise the model overlay the
data in 2-D and high-dimensional space. Furthermore, provides
summaries and diagnostics to evaluate the nonlinear dimension
reduction layout.

Jayani P. G. Lakshika

quollr

Visualising How Nonlinear Dimension Reduction Warps Your Data

Jayani P. Gamage

Dianne Cook

Paul Harrison

Michael Lydeamore

Thiyanga S. Talagala

augment function

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

Arguments

Augment Data with Predictions and Error Metrics — augment

<dl>

<dt>highd_data</dt>
<dd>The dataset containing high-dimensional coordinates and an unique identifier.</dd>


<dt>model_2d</dt>
<dd>Centroid coordinates of hexagonal bins in 2-D space.</dd>


<dt>model_highd</dt>
<dd>Centroid coordinates of hexagonal bins in high dimensions.</dd>

</dl>

augment: Augment Data with Predictions and Error Metrics

Description

Usage

Value

Arguments

Examples