Journal Highlight: On the use of the observation-wise k-fold operation in PCA cross-validation

Skip to Navigation

Ezine

  • Published: Sep 14, 2015
  • Author: spectroscopyNOW
  • Channels: Chemometrics & Informatics
thumbnail image: Journal Highlight: On the use of the observation-wise <em>k</em>-fold operation in PCA cross-validation
A powerful imaging tool for analysis of heterogeneous gene expression together with upstream signaling in live single cells was developed by combining fluorescence and bioluminescence microscopy.

On the use of the observation-wise k-fold operation in PCA cross-validation

Journal of Chemometrics, 2015, 29, 467-478
Edoardo Saccenti and José Camacho

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 observation-wise 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.

  • This paper is free to view for all users registered on spectroscopyNOW.com until the end of October 2015.
    After this time, you can purchase it using Pay-Per-View on Wiley Online Library.

Follow us on Twitter!

Social Links

Share This Links

Bookmark and Share

Microsites

Suppliers Selection
Societies Selection

Banner Ad

Click here to see
all job opportunities

Copyright Information

Interested in separation science? Visit our sister site separationsNOW.com

Copyright © 2017 John Wiley & Sons, Inc. All Rights Reserved