On the use of \(t\)-distributed stochastic neighbor embedding for data visualization and classification of individuals with Parkinson's disease

DOI10.1155/2018/8019232zbMath1431.92065DBLPjournals/cmmm/OliveiraMA18OpenAlexW2899502658WikidataQ59806685 ScholiaQ59806685MaRDI QIDQ1728841

Adriano O. Andrade, Alessandro R. P. Machado, Fábio Henrique M. Oliveira

Publication date: 26 February 2019

Published in: Computational \& Mathematical Methods in Medicine (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1155/2018/8019232

zbMATH Keywords

Parkinson's disease\(t\)-distributed stochastic neighbor embeddingdata visualization and classification

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Learning and adaptive systems in artificial intelligence (68T05) Medical applications (general) (92C50)

Related Items (1)

Conceptual and empirical comparison of dimensionality reduction algorithms (PCA, KPCA, LDA, MDS, SVD, LLE, ISOMAP, LE, ICA, t-SNE)

Uses Software

• t-SNE

Cites Work

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• Model-based clustering of high-dimensional data: a review
• Support-vector networks
• A General Framework for Dimensionality-Reducing Data Visualization Mapping

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