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- Elastic_map abstract "Elastic maps provide a tool for nonlinear dimensionality reduction. By their construction, they are a system of elastic springs embedded in the dataspace. This system approximates a low-dimensional manifold. The elastic coefficients of this system allow the switch from completely unstructured k-means clustering (zero elasticity) to the estimators located closely to linear PCA manifolds (for high bending and low stretching modules). With some intermediate values of the elasticity coefficients, this system effectively approximates non-linear principal manifolds. This approach is based on a mechanical analogy between principal manifolds, that are passing through "the middle" of the data distribution, and elastic membranes and plates. The method was developed by A.N. Gorban, A.Y. Zinovyev and A.A. Pitenko in 1996–1998.".
- Elastic_map thumbnail Elmap_breastcancer_wiki.png?width=300.
- Elastic_map wikiPageID "28476914".
- Elastic_map wikiPageRevisionID "601193729".
- Elastic_map hasPhotoCollection Elastic_map.
- Elastic_map subject Category:Data_mining.
- Elastic_map subject Category:Dimension_reduction.
- Elastic_map subject Category:Multivariate_statistics.
- Elastic_map comment "Elastic maps provide a tool for nonlinear dimensionality reduction. By their construction, they are a system of elastic springs embedded in the dataspace. This system approximates a low-dimensional manifold. The elastic coefficients of this system allow the switch from completely unstructured k-means clustering (zero elasticity) to the estimators located closely to linear PCA manifolds (for high bending and low stretching modules).".
- Elastic_map label "Elastic map".
- Elastic_map label "Упругая карта".
- Elastic_map sameAs m.0crjfd7.
- Elastic_map sameAs Q4476452.
- Elastic_map sameAs Q4476452.
- Elastic_map wasDerivedFrom Elastic_map?oldid=601193729.
- Elastic_map depiction Elmap_breastcancer_wiki.png.
- Elastic_map isPrimaryTopicOf Elastic_map.
