Abstract
In this paper we analyze the problem of variance inflation experienced by the PCA algorithm when working in an ill-posed scenario where the dimensionality of the training set is larger than its sample size. In an earlier article a correction method based on a Leave-One-Out (LOO) procedure was introduced. We propose a Hold-out procedure whose computational cost is lower and, unlike the LOO method, the number of SVD's does not scale with the sample size. We analyze its properties from a theoretical and empirical point of view. Finally we apply it to a real classification scenario.
Original language | English |
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Title of host publication | 2012 3rd International Workshop on Cognitive Information Processing (CIP) |
Number of pages | 6 |
Publisher | IEEE |
Publication date | 2012 |
ISBN (Print) | 978-1-4673-1877-8 |
DOIs | |
Publication status | Published - 2012 |
Event | 3rd International Workshop on Cognitive Information Processing (CIP) - Baiona, Spain Duration: 28 May 2012 → 30 May 2012 http://cip2012.tsc.uc3m.es/ |
Workshop
Workshop | 3rd International Workshop on Cognitive Information Processing (CIP) |
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Country/Territory | Spain |
City | Baiona |
Period | 28/05/2012 → 30/05/2012 |
Internet address |