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- Nonlinear_dimensionality_reduction abstract "High-dimensional data, meaning data that requires more than two or three dimensions to represent, can be difficult to interpret. One approach to simplification is to assume that the data of interest lie on an embedded non-linear manifold within the higher-dimensional space. If the manifold is of low enough dimension, the data can be visualised in the low-dimensional space.Below is a summary of some of the important algorithms from the history of manifold learning and nonlinear dimensionality reduction (NLDR). Many of these non-linear dimensionality reduction methods are related to the linear methods listed below. Non-linear methods can be broadly classified into two groups: those that provide a mapping (either from the high-dimensional space to the low-dimensional embedding or vice versa), and those that just give a visualisation. In the context of machine learning, mapping methods may be viewed as a preliminary feature extraction step, after which pattern recognition algorithms are applied. Typically those that just give a visualisation are based on proximity data – that is, distance measurements.".
- Nonlinear_dimensionality_reduction thumbnail Lle_hlle_swissroll.png?width=300.
- Nonlinear_dimensionality_reduction wikiPageExternalLink isomap.stanford.edu.
- Nonlinear_dimensionality_reduction wikiPageExternalLink edrt.
- Nonlinear_dimensionality_reduction wikiPageExternalLink DD-HDS-homepage.html.
- Nonlinear_dimensionality_reduction wikiPageExternalLink RankVisu-homepage.html.
- Nonlinear_dimensionality_reduction wikiPageExternalLink diffusion_maps.pdf.
- Nonlinear_dimensionality_reduction wikiPageExternalLink waffles.sourceforge.net.
- Nonlinear_dimensionality_reduction wikiPageExternalLink www.VisuMap.com.
- Nonlinear_dimensionality_reduction wikiPageExternalLink lle.
- Nonlinear_dimensionality_reduction wikiPageExternalLink gplvm.
- Nonlinear_dimensionality_reduction wikiPageExternalLink thesis.htm.
- Nonlinear_dimensionality_reduction wikiPageExternalLink GTM.
- Nonlinear_dimensionality_reduction wikiPageExternalLink www.nlpca.org.
- Nonlinear_dimensionality_reduction wikiPageExternalLink RpmOverview.
- Nonlinear_dimensionality_reduction wikiPageID "309261".
- Nonlinear_dimensionality_reduction wikiPageRevisionID "604224500".
- Nonlinear_dimensionality_reduction hasPhotoCollection Nonlinear_dimensionality_reduction.
- Nonlinear_dimensionality_reduction subject Category:Dimension.
- Nonlinear_dimensionality_reduction subject Category:Dimension_reduction.
- Nonlinear_dimensionality_reduction subject Category:Multivariate_statistics.
- Nonlinear_dimensionality_reduction comment "High-dimensional data, meaning data that requires more than two or three dimensions to represent, can be difficult to interpret. One approach to simplification is to assume that the data of interest lie on an embedded non-linear manifold within the higher-dimensional space.".
- Nonlinear_dimensionality_reduction label "Nonlinear dimensionality reduction".
- Nonlinear_dimensionality_reduction sameAs m.01sz4s.
- Nonlinear_dimensionality_reduction sameAs Q7049464.
- Nonlinear_dimensionality_reduction sameAs Q7049464.
- Nonlinear_dimensionality_reduction wasDerivedFrom Nonlinear_dimensionality_reduction?oldid=604224500.
- Nonlinear_dimensionality_reduction depiction Lle_hlle_swissroll.png.
- Nonlinear_dimensionality_reduction isPrimaryTopicOf Nonlinear_dimensionality_reduction.
