Rdimtools: An R package for Dimension Reduction and Intrinsic Dimension Estimation

05/22/2020
by   Kisung You, et al.
0

Discovering patterns of the complex high-dimensional data is a long-standing problem. Dimension Reduction (DR) and Intrinsic Dimension Estimation (IDE) are two fundamental thematic programs that facilitate geometric understanding of the data. We present Rdimtools - an R package that supports 133 DR and 17 IDE algorithms whose extent makes multifaceted scrutiny of the data in one place easier. Rdimtools is distributed under the MIT license and is accessible from CRAN, GitHub, and its package website, all of which deliver instruction for installation, self-contained examples, and API documentation.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
03/11/2021

Modern Dimension Reduction

Data are not only ubiquitous in society, but are increasingly complex bo...
research
09/24/2019

Dimension Estimation Using Autoencoders

Dimension Estimation (DE) and Dimension Reduction (DR) are two closely r...
research
10/13/2022

An Additive Autoencoder for Dimension Estimation

An additive autoencoder for dimension reduction, which is composed of a ...
research
02/23/2021

intRinsic: an R package for model-based estimation of the intrinsic dimension of a dataset

The estimation of the intrinsic dimension of a dataset is a fundamental ...
research
01/31/2022

A Probabilistic Graph Coupling View of Dimension Reduction

Most popular dimension reduction (DR) methods like t-SNE and UMAP are ba...
research
03/15/2020

Hierarchical Models: Intrinsic Separability in High Dimensions

It has long been noticed that high dimension data exhibits strange patte...
research
10/17/2021

Persuasion by Dimension Reduction

How should an agent (the sender) observing multi-dimensional data (the s...

Please sign up or login with your details

Forgot password? Click here to reset