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Nonlinear dimensionality reduction

Nonlinear dimensionality reduction (NLDR), also known as manifold learning, is any of various related techniques that aim to project high-dimensional data, potentially existing across non-linear manifolds (non-affine subspaces) which cannot be adequately captured by linear decomposition methods, onto lower-dimensional latent manifolds, with the goal of…

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Applications of NLDR

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Other algorithms

Methods based on proximity matrices

Software

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Nonlinear dimensionality reduction

Nodes91
Edges90
Triples35
Avg. degree1.98
Density0.021978
Components1

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Nonlinear dimensionality reduction

Top relations

related to Laplacian eigenmaps · 13
Nonlinear dimensionality reduction → Attempts, Beltrami, Each, Fourier, Hilbert, Laplace, Laplacian, Minimization, Reproducing, Such, The, This, Traditional
has application · 10
Nonlinear dimensionality reduction → Each, For, Hamming, High, Information, It, Nonlinear, Reducing, The, This
related to Principal curves and manifolds · 8
Nonlinear dimensionality reduction → How, Kohonen's SOM, PCA, Principal, The, This, Trevor Hastie, Usually
related to Uniform manifold approximation and projection · 4
Nonlinear dimensionality reduction → It, SNE, UMAP, Uniform

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Important terminology

manifold data points space displaystyle embedding algorithm point dimensionality reduction linear mapping isomap matrix kernel distance model map local based

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SubjectPredicateObjectConfidenceSrc
Nonlinear dimensionality reductionhas applicationHigh0.60section
Nonlinear dimensionality reductionhas applicationIt0.60section
Nonlinear dimensionality reductionhas applicationReducing0.60section
Nonlinear dimensionality reductionhas applicationThe0.60section
Nonlinear dimensionality reductionhas applicationThis0.60section
Nonlinear dimensionality reductionhas applicationFor0.60section
Nonlinear dimensionality reductionhas applicationEach0.60section
Nonlinear dimensionality reductionhas applicationHamming0.60section
Nonlinear dimensionality reductionhas applicationInformation0.60section
Nonlinear dimensionality reductionhas applicationNonlinear0.60section
Nonlinear dimensionality reductionrelated to Laplacian eigenmapsLaplacian0.60section
Nonlinear dimensionality reductionrelated to Laplacian eigenmapsThis0.60section

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