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

Title
Conceptual and empirical comparison of dimensionality reduction algorithms (PCA, KPCA, LDA, MDS, SVD, LLE, ISOMAP, LE, ICA, t-SNE)
Authors
Keywords
Dimension reduction, Optimal set of features, Data quality, High-dimensional datasets, Correlation metrics, Classification accuracy, Run-time
Journal
Computer Science Review
Volume 40, Issue -, Pages 100378
Publisher
Elsevier BV
Online
2021-02-22
DOI
10.1016/j.cosrev.2021.100378

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