A leave-K-out cross-validation scheme for unsupervised kernel regression

Klanke S, Ritter H (2006)
In: ARTIFICIAL NEURAL NETWORKS - ICANN 2006, PT 2. Lecture notes in computer science, 4132. SPRINGER-VERLAG BERLIN: 427-436.

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Konferenzbeitrag | Veröffentlicht | Englisch
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Abstract / Bemerkung
We show how to employ leave-K-out cross-validation in Unsupervised Kernel Regression, a recent method for learning of nonlinear manifolds. We thereby generalize an already present regularization method, yielding more flexibility without additional computational cost. We demonstrate our method on both toy and real data.
Erscheinungsjahr
Titel des Konferenzbandes
ARTIFICIAL NEURAL NETWORKS - ICANN 2006, PT 2
Band
4132
Seite
427-436
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Klanke S, Ritter H. A leave-K-out cross-validation scheme for unsupervised kernel regression. In: ARTIFICIAL NEURAL NETWORKS - ICANN 2006, PT 2. Lecture notes in computer science. Vol 4132. SPRINGER-VERLAG BERLIN; 2006: 427-436.
Klanke, S., & Ritter, H. (2006). A leave-K-out cross-validation scheme for unsupervised kernel regression. ARTIFICIAL NEURAL NETWORKS - ICANN 2006, PT 2, Lecture notes in computer science, 4132, 427-436. SPRINGER-VERLAG BERLIN.
Klanke, S., and Ritter, H. (2006). “A leave-K-out cross-validation scheme for unsupervised kernel regression” in ARTIFICIAL NEURAL NETWORKS - ICANN 2006, PT 2 Lecture notes in computer science, vol. 4132, (SPRINGER-VERLAG BERLIN), 427-436.
Klanke, S., & Ritter, H., 2006. A leave-K-out cross-validation scheme for unsupervised kernel regression. In ARTIFICIAL NEURAL NETWORKS - ICANN 2006, PT 2. Lecture notes in computer science. no.4132 SPRINGER-VERLAG BERLIN, pp. 427-436.
S. Klanke and H. Ritter, “A leave-K-out cross-validation scheme for unsupervised kernel regression”, ARTIFICIAL NEURAL NETWORKS - ICANN 2006, PT 2, Lecture notes in computer science, vol. 4132, SPRINGER-VERLAG BERLIN, 2006, pp.427-436.
Klanke, S., Ritter, H.: A leave-K-out cross-validation scheme for unsupervised kernel regression. ARTIFICIAL NEURAL NETWORKS - ICANN 2006, PT 2. Lecture notes in computer science. 4132, p. 427-436. SPRINGER-VERLAG BERLIN (2006).
Klanke, Stefan, and Ritter, Helge. “A leave-K-out cross-validation scheme for unsupervised kernel regression”. ARTIFICIAL NEURAL NETWORKS - ICANN 2006, PT 2. SPRINGER-VERLAG BERLIN, 2006.Vol. 4132. Lecture notes in computer science. 427-436.