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• CRAN
• Wiki
• Wiki
• sklearn
• Wiki
• Code
• Code
• A survey of dimensionality reduction techniques
• Feature Selection and Feature Extraction in Pattern Analysis: A Literature Review
• On lines and planes of closest fit to systems of points in space
• Prediction by Supervised Principal Components
• sklearn
• sklearn
• Nonlinear Component Analysis as a Kernel Eigenvalue Problem - Robert Muller*
• Kernel PCA for Novelty Detection
• Robust Kernel Principal Component Analysis
• CRAN - learn.org/stable/modules/generated/sklearn.decomposition.IncrementalPCA.html#sklearn.decomposition.IncrementalPCA))
• Wiki
• Independent Component Analysis - Free ebook *Aapo Hyvarinen, Juha Karhunen, Erkki Oja*
• Wiki
• The Utilization of Multiple Measurements in Problems of Biological Classification - require registration *C. Radhakrishna Rao*
• CRAN
• Wiki
• Multidimensional scaling by optimizing goodness of fit to a nonmetric hypothesis
• An Analysis of Classical Multidimensional Scaling
• Online Learning for Latent Dirichlet Allocation
• Wiki - learn.org/stable/modules/generated/sklearn.decomposition.FactorAnalysis.html#sklearn.decomposition.FactorAnalysis))
• Homepage - distributed_stochastic_neighbor_embedding), [CRAN](https://cran.r-project.org/web/packages/tsne/), [sklearn](https://scikit-learn.org/stable/modules/generated/sklearn.manifold.TSNE.html))
• Visualizing Data using t-SNE
• Accelerating t-SNE using Tree-Based Algorithms
• Code
• Tree-SNE: Hierarchical Clustering and Visualization Using t-SNE - Hoffman*
• Let-SNE: A Hybrid Approach to Data Embedding and Visualization of Hyperspectral Imagery
• UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction
• Trimap: Large-scale Dimensionality Reduction Using Triplets
• Self-Organized Formation of Topologically Correct Feature Maps
• Visualizing Large-scale and High-dimensional Data
• Paper - project.org/web/packages/Rdimtools/))
• Prediction by Supervised Principal Components
• Nonlinear Component Analysis as a Kernel Eigenvalue Problem - Robert Muller*
• Multidimensional scaling by optimizing goodness of fit to a nonmetric hypothesis
• A survey of dimensionality reduction techniques
• On lines and planes of closest fit to systems of points in space
• Kernel PCA for Novelty Detection
• Robust Kernel Principal Component Analysis
• Independent Component Analysis: Algorithms and Applications
• The Use of Multiple Measurements in Taxonomic Problems
• PCA versus LDA
• An Analysis of Classical Multidimensional Scaling
• Homepage
• A Global Geometric Framework for Nonlinear Dimensionality Reduction
• Let-SNE: A Hybrid Approach to Data Embedding and Visualization of Hyperspectral Imagery
• Trimap: Large-scale Dimensionality Reduction Using Triplets
• Self-Organized Formation of Topologically Correct Feature Maps