UID:
almahu_9949972393002882
Umfang:
X, 209 p.
,
online resource.
Ausgabe:
1st ed. 2006.
ISBN:
9783540341383
Serie:
Theoretical Computer Science and General Issues, 3940
Anmerkung:
Invited Contributions -- Discrete Component Analysis -- Overview and Recent Advances in Partial Least Squares -- Random Projection, Margins, Kernels, and Feature-Selection -- Some Aspects of Latent Structure Analysis -- Feature Selection for Dimensionality Reduction -- Contributed Papers -- Auxiliary Variational Information Maximization for Dimensionality Reduction -- Constructing Visual Models with a Latent Space Approach -- Is Feature Selection Still Necessary? -- Class-Specific Subspace Discriminant Analysis for High-Dimensional Data -- Incorporating Constraints and Prior Knowledge into Factorization Algorithms - An Application to 3D Recovery -- A Simple Feature Extraction for High Dimensional Image Representations -- Identifying Feature Relevance Using a Random Forest -- Generalization Bounds for Subspace Selection and Hyperbolic PCA -- Less Biased Measurement of Feature Selection Benefits.
In:
Springer Nature eBook
Weitere Ausg.:
Printed edition: ISBN 9783540341376
Weitere Ausg.:
Printed edition: ISBN 9783540823810
Sprache:
Englisch
URL:
https://doi.org/10.1007/11752790
