Uncovering High-dimensional Structures of Projections from Dimensionality Reduction Methods

Uncovering High-dimensional Structures of Projections from Dimensionality Reduction Methods

Projections are conventional methods of dimensionality reduction for information visualization used to transform high-dimensional data into low dimensional space. If the projection method restricts the output space to two dimensions, the result is a scatter plot. The goal of this scatter plot is to...

Full description

Bibliographic Details
Main Authors:	Michael C. Thrun, PhD, Alfred Ultsch, Prof. Dr. habil.
Format:	Article
Language:	English
Published:	Elsevier 2020-01-01
Series:	MethodsX
Subjects:	Dimensionality reduction Projection methods Data visualization Unsupervised neural networks Self-organizing maps
Online Access:	http://www.sciencedirect.com/science/article/pii/S2215016120303137

Similar Items

Analyzing Quality Measurements for Dimensionality Reduction
by: Michael C. Thrun, et al.
Published: (2023-08-01)

Evaluation of projections, obtained by dimensionality reduction techniques
by: Kotryna Paulauskienė, et al.
Published: (2014-12-01)

Learning Neural Representations and Local Embedding for Nonlinear Dimensionality Reduction Mapping
by: Sheng-Shiung Wu, et al.
Published: (2021-04-01)

Improving Dimensionality Reduction Projections for Data Visualization
by: Bardia Rafieian, et al.
Published: (2023-09-01)

Dimensionality Reduction by Similarity Distance-Based Hypergraph Embedding
by: Xingchen Shen, et al.
Published: (2022-09-01)

Linear and Non-linear Dimensionality-Reduction Techniques on Full Hand Kinematics
by: Alexandra A. Portnova-Fahreeva, et al.
Published: (2020-05-01)

Robust Locality Preserving Projections With Cosine-Based Dissimilarity for Linear Dimensionality Reduction
by: Qiang Yu, et al.
Published: (2017-01-01)

Is Unsupervised Dimensionality Reduction Sufficient to Decode the Complexities of Electrochemical Impedance Spectra?
by: Aleksei Makogon, et al.
Published: (2024-04-01)

Dimensionality Reduction of Tensors Based on Local Homeomorphism and Global Subspace Projection Distance Minimum
by: Guokai Zhang, et al.
Published: (2020-01-01)

Quantitative and Qualitative Comparison of 2D and 3D Projection Techniques for High-Dimensional Data
by: Zonglin Tian, et al.
Published: (2021-06-01)

Supervised Dimensionality Reduction of Hyperspectral Imagery Via Local and Global Sparse Representation
by: Faxian Cao, et al.
Published: (2021-01-01)

Evolution of SOMs’ Structure and Learning Algorithm: From Visualization of High-Dimensional Data to Clustering of Complex Data
by: Marian B. Gorzałczany, et al.
Published: (2020-04-01)

Mixing Autoencoder With Classifier: Conceptual Data Visualization
by: Pitoyo Hartono
Published: (2020-01-01)

Vigilance associates with the low-dimensional structure of fMRI data
by: Shengchao Zhang, et al.
Published: (2023-02-01)

Dimensionality reduction of hyperspectral images of vegetation and crops based on self-organized maps
by: David Ruiz Hidalgo, et al.
Published: (2021-06-01)

One-Layer vs. Two-Layer SOM in the Context of Outlier Identification: A Simulation Study
by: Gabriel Antonio Valverde Castilla, et al.
Published: (2021-07-01)

Artificial Intelligence and Dimensionality Reduction: Tools for Approaching Future Communications
by: Alejandro Ramirez-Arroyo, et al.
Published: (2022-01-01)

Efficient High-Dimensional Kernel k-Means++ with Random Projection
by: Jan Y. K. Chan, et al.
Published: (2021-07-01)

Multi-View Projection Learning via Adaptive Graph Embedding for Dimensionality Reduction
by: Haohao Li, et al.
Published: (2023-07-01)

Numerical Demonstration of Unsupervised-Learning-Based Noise Reduction in Two-Dimensional Rayleigh Imaging
by: Minnan Cai, et al.
Published: (2022-08-01)

Dimensionality reduction methods for extracting functional networks from large‐scale CRISPR screens
by: Arshia Zernab Hassan, et al.
Published: (2023-11-01)

Morphological mapping for non‐linear dimensionality reduction
by: Rajiv Kapoor, et al.
Published: (2015-04-01)

On the Classification of ECG and EEG Signals with Various Degrees of Dimensionality Reduction
by: Monica Fira, et al.
Published: (2021-05-01)

Hyperspectral Dimensionality Reduction Based on Multiscale Superpixelwise Kernel Principal Component Analysis
by: Lan Zhang, et al.
Published: (2019-05-01)

Dynamical Analysis of the Dow Jones Index Using Dimensionality Reduction and Visualization
by: António M. Lopes, et al.
Published: (2021-05-01)

Context-flexible cartography with Siamese topological neural networks
by: Pitoyo Hartono
Published: (2024-01-01)

Dimensionality Reduction for Smart IoT Sensors
by: Jorge Vizárraga, et al.
Published: (2020-12-01)

Getting over High-Dimensionality: How Multidimensional Projection Methods Can Assist Data Science
by: Evandro S. Ortigossa, et al.
Published: (2022-07-01)

direpack: A Python 3 package for state-of-the-art statistical dimensionality reduction methods
by: Emmanuel Jordy Menvouta, et al.
Published: (2023-02-01)

Sparse Low-Rank Preserving Projection for Dimensionality Reduction
by: Zhonghua Liu, et al.
Published: (2019-01-01)

Novel Data-Driven Spatial-Spectral Correlated Scheme for Dimensionality Reduction of Hyperspectral Images
by: Yanming Zhang, et al.
Published: (2022-01-01)

Robust Covariance Representations With Large Margin Dimensionality Reduction for Visual Classification
by: Qiule Sun, et al.
Published: (2018-01-01)

Feature Selection for the Prediction Model of the Tehran Stock Exchange Index by Dimensionality Reduction Techniques
by: Somayeh Mohebi, et al.
Published: (2022-12-01)

Approaching Optimal Nonlinear Dimensionality Reduction by a Spiking Neural Network
by: Álvaro Anzueto-Ríos, et al.
Published: (2021-07-01)

Two-Stage Dimensionality Reduction for Social Media Engagement Classification
by: Jose Luis Vieira Sobrinho, et al.
Published: (2024-02-01)

Using bi-dimensional representations to understand patterns in COVID-19 blood exam data
by: Vitor P. Bezzan, et al.
Published: (2022-01-01)

Deep Self-Organizing Map of Convolutional Layers for Clustering and Visualizing Image Data
by: Christos Ferles, et al.
Published: (2021-11-01)

A Self-Organized Mapping Neural Network-Based Intelligent Evaluation Model for Business Capacity in Enterprise Management
by: Qi Zhang, et al.
Published: (2023-01-01)

Analysis and convergence of weighted dimensionality reduction methods
by: Juan Carlos Riaño Rojas, et al.
Published: (2013-02-01)

Neighbors-Based Graph Construction for Dimensionality Reduction
by: Hui Tian, et al.
Published: (2019-01-01)