%0 Book Section %1 todorov2013comparing %A Todorov, Valentin %A Filzmoser, Peter %B Synergies of Soft Computing and Statistics for Intelligent Data Analysis %D 2013 %E Kruse, Rudolf %E Berthold, Michael R. %E Moewes, Christian %E Gil, María Ángeles %E Grzegorzewski, Przemysław %E Hryniewicz, Olgierd %I Springer Berlin Heidelberg %K pca r robust sparse todorov %P 283-291 %R 10.1007/978-3-642-33042-1_31 %T Comparing Classical and Robust Sparse PCA %U http://dx.doi.org/10.1007/978-3-642-33042-1_31 %V 190 %X The main drawback of principal component analysis (PCA) especially for applications in high dimensions is that the extracted components are linear combinations of all input variables. To facilitate the interpretability of PCA various sparse methods have been proposed recently. However all these methods might suffer from the influence of outliers present in the data. An algorithm to compute sparse and robust PCA was recently proposed by Croux %@ 978-3-642-33041-4

@incollection{todorov2013comparing, abstract = {The main drawback of principal component analysis (PCA) especially for applications in high dimensions is that the extracted components are linear combinations of all input variables. To facilitate the interpretability of PCA various sparse methods have been proposed recently. However all these methods might suffer from the influence of outliers present in the data. An algorithm to compute sparse and robust PCA was recently proposed by Croux }, added-at = {2013-02-02T23:54:14.000+0100}, author = {Todorov, Valentin and Filzmoser, Peter}, biburl = {https://www.bibsonomy.org/bibtex/2615bc8eca6931ed430ef3808cddb5340/vivion}, booktitle = {Synergies of Soft Computing and Statistics for Intelligent Data Analysis}, description = {Comparing Classical and Robust Sparse PCA - Springer}, doi = {10.1007/978-3-642-33042-1_31}, editor = {Kruse, Rudolf and Berthold, Michael R. and Moewes, Christian and Gil, María Ángeles and Grzegorzewski, Przemysław and Hryniewicz, Olgierd}, interhash = {22ab82fa719a3f93e58f04072eaf76de}, intrahash = {615bc8eca6931ed430ef3808cddb5340}, isbn = {978-3-642-33041-4}, keywords = {pca r robust sparse todorov}, pages = {283-291}, publisher = {Springer Berlin Heidelberg}, series = {Advances in Intelligent Systems and Computing}, timestamp = {2013-02-02T23:55:36.000+0100}, title = {Comparing Classical and Robust Sparse PCA}, url = {http://dx.doi.org/10.1007/978-3-642-33042-1_31}, volume = 190, year = 2013 }