An iterative approach to local-PCA

John S, Wersing H, Ritter H (2010)
In: Neural Networks (IJCNN), The 2010 International Joint Conference on. 1-6.

Konferenzbeitrag | Veröffentlicht | Englisch
 
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Abstract / Bemerkung
We introduce a greedy algorithm that works from coarse to fine by iteratively applying localized principal component analysis (PCA). The decision where and when to split or add new components is based on two antagonistic criteria. Firstly, the well known quadratic reconstruction error and secondly a measure for the homogeneity of the distribution. For the latter criterion, which we call #x201C;generation error #x201D;, we compared two different possible methods to assess if the data samples are distributed homogeneously. The proposed algorithm does not involve a costly multi-objective optimization to find a partition of the inputs. Further, the final number of local PCA units, as well as their individual dimensionality need not to be predefined. We demonstrate that the method can flexibly react to different intrinsic dimensionalities of the data.
Stichworte
distribution homogeneity; antagonistic criteria; generation error; greedy algorithm; iterative approach; quadratic reconstruction error; localized principal component analysis; greedy algorithms; iterative methods; principal component analysis
Erscheinungsjahr
2010
Titel des Konferenzbandes
Neural Networks (IJCNN), The 2010 International Joint Conference on
Seite(n)
1-6
Konferenz
IJCNN
Konferenzort
Barcelona
Konferenzdatum
2010-07-19
ISBN
978-1-4244-6916-1
ISSN
1098-7576
Page URI
https://pub.uni-bielefeld.de/record/2376395

Zitieren

John S, Wersing H, Ritter H. An iterative approach to local-PCA. In: Neural Networks (IJCNN), The 2010 International Joint Conference on. 2010: 1-6.
John, S., Wersing, H., & Ritter, H. (2010). An iterative approach to local-PCA. Neural Networks (IJCNN), The 2010 International Joint Conference on, 1-6. doi:10.1109/IJCNN.2010.5596615
John, S., Wersing, H., and Ritter, H. (2010). “An iterative approach to local-PCA” in Neural Networks (IJCNN), The 2010 International Joint Conference on 1-6.
John, S., Wersing, H., & Ritter, H., 2010. An iterative approach to local-PCA. In Neural Networks (IJCNN), The 2010 International Joint Conference on. pp. 1-6.
S. John, H. Wersing, and H. Ritter, “An iterative approach to local-PCA”, Neural Networks (IJCNN), The 2010 International Joint Conference on, 2010, pp.1-6.
John, S., Wersing, H., Ritter, H.: An iterative approach to local-PCA. Neural Networks (IJCNN), The 2010 International Joint Conference on. p. 1-6. (2010).
John, Samuel, Wersing, Heiko, and Ritter, Helge. “An iterative approach to local-PCA”. Neural Networks (IJCNN), The 2010 International Joint Conference on. 2010. 1-6.

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