ISOLLE: Locally linear embedding with geodesic distance

Varini C, Degenhard A, Nattkemper TW (2005)
In: KNOWLEDGE DISCOVERY IN DATABASES: PKDD 2005. Jorge A (Ed); Lecture notes in computer science ; 3721 : Lecture notes in artificial intelligence, 3721. Berlin, Heidelberg: SPRINGER-VERLAG BERLIN: 331-342.

Konferenzbeitrag | Veröffentlicht | Englisch
 
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Autor*in
Varini, C; Degenhard, A; Nattkemper, Tim WilhelmUniBi
Herausgeber*in
Jorge, Alípio
Abstract / Bemerkung
Locally Linear Embedding (LLE) has recently been proposed as a method for dimensional reduction of high-dimensional nonlinear data sets. In LLE each data point is reconstructed from a linear combination of its n nearest neighbors, which are typically found using the Euclidean Distance. We propose an extension of LLE which consists in performing the search for the neighbors with respect to the geodesic distance (ISOLLE). In this study we show that the usage of this metric can lead to a more accurate preservation of the data structure. The proposed approach is validated on both real-world and synthetic data.
Erscheinungsjahr
2005
Titel des Konferenzbandes
KNOWLEDGE DISCOVERY IN DATABASES: PKDD 2005
Band
3721
Seite(n)
331-342
ISBN
9783540292449
ISSN
0302-9743
Page URI
https://pub.uni-bielefeld.de/record/1601519

Zitieren

Varini C, Degenhard A, Nattkemper TW. ISOLLE: Locally linear embedding with geodesic distance. In: Jorge A, ed. KNOWLEDGE DISCOVERY IN DATABASES: PKDD 2005. Lecture notes in computer science ; 3721 : Lecture notes in artificial intelligence. Vol 3721. Berlin, Heidelberg: SPRINGER-VERLAG BERLIN; 2005: 331-342.
Varini, C., Degenhard, A., & Nattkemper, T. W. (2005). ISOLLE: Locally linear embedding with geodesic distance. In A. Jorge (Ed.), Lecture notes in computer science ; 3721 : Lecture notes in artificial intelligence: Vol. 3721. KNOWLEDGE DISCOVERY IN DATABASES: PKDD 2005 (pp. 331-342). Berlin, Heidelberg: SPRINGER-VERLAG BERLIN. doi:10.1007/11564126_34
Varini, C., Degenhard, A., and Nattkemper, T. W. (2005). “ISOLLE: Locally linear embedding with geodesic distance” in KNOWLEDGE DISCOVERY IN DATABASES: PKDD 2005, Jorge, A. ed. Lecture notes in computer science ; 3721 : Lecture notes in artificial intelligence, vol. 3721, (Berlin, Heidelberg: SPRINGER-VERLAG BERLIN), 331-342.
Varini, C., Degenhard, A., & Nattkemper, T.W., 2005. ISOLLE: Locally linear embedding with geodesic distance. In A. Jorge, ed. KNOWLEDGE DISCOVERY IN DATABASES: PKDD 2005. Lecture notes in computer science ; 3721 : Lecture notes in artificial intelligence. no.3721 Berlin, Heidelberg: SPRINGER-VERLAG BERLIN, pp. 331-342.
C. Varini, A. Degenhard, and T.W. Nattkemper, “ISOLLE: Locally linear embedding with geodesic distance”, KNOWLEDGE DISCOVERY IN DATABASES: PKDD 2005, A. Jorge, ed., Lecture notes in computer science ; 3721 : Lecture notes in artificial intelligence, vol. 3721, Berlin, Heidelberg: SPRINGER-VERLAG BERLIN, 2005, pp.331-342.
Varini, C., Degenhard, A., Nattkemper, T.W.: ISOLLE: Locally linear embedding with geodesic distance. In: Jorge, A. (ed.) KNOWLEDGE DISCOVERY IN DATABASES: PKDD 2005. Lecture notes in computer science ; 3721 : Lecture notes in artificial intelligence. 3721, p. 331-342. SPRINGER-VERLAG BERLIN, Berlin, Heidelberg (2005).
Varini, C, Degenhard, A, and Nattkemper, Tim Wilhelm. “ISOLLE: Locally linear embedding with geodesic distance”. KNOWLEDGE DISCOVERY IN DATABASES: PKDD 2005. Ed. Alípio Jorge. Berlin, Heidelberg: SPRINGER-VERLAG BERLIN, 2005.Vol. 3721. Lecture notes in computer science ; 3721 : Lecture notes in artificial intelligence. 331-342.

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