Staff Publications

Staff Publications

  • external user (warningwarning)
  • Log in as
  • language uk
  • About

    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

    We have a manual that explains all the features 

Record number 491226
Title On the use of the observation-wise k-fold operation in PCA cross-validation
Author(s) Saccenti, E.; Camacho, J.
Source Journal of Chemometrics 29 (2015)8. - ISSN 0886-9383 - p. 467 - 478.
DOI https://doi.org/10.1002/cem.2726
Department(s) Systems and Synthetic Biology
VLAG
Publication type Refereed Article in a scientific journal
Publication year 2015
Keyword(s) principal component analysis - missing data - models - number - spectroscopy - mspc - pls
Abstract Cross-validation (CV) is a common approach for determining the optimal number of components in a principal component analysis model. To guarantee the independence between model testing and calibration, the observationwise k-fold operation is commonly implemented in each cross-validation step. This operation renders the CV algorithm computationally intensive, and it is the main limitation to apply CV on very large data sets. In this paper, we carry out an empirical and theoretical investigation of the use of this operation in the element-wise k-fold (ekf) algorithm, the state-of-the-art CV algorithm. We show that when very large data sets need to be cross-validated and the computational time is a matter of concern, the observation-wise k-fold operation can be skipped. The theoretical properties of the resulting modified algorithm, referred to as column-wise k-fold (ckf) algorithm, are derived. Also, its performance is evaluated with several artificial and real data sets. We suggest the ckf algorithm to be a valid alternative to the standard ekf to reduce the computational time needed to cross-validate a data set
Comments
There are no comments yet. You can post the first one!
Post a comment
 
Please log in to use this service. Login as Wageningen University & Research user or guest user in upper right hand corner of this page.