The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
PLS Dimension Reduction for Classification with Microarray Data
Open accessAbstract
Partial Least Squares (PLS) dimension reduction is known to give good prediction accuracy in the context of classification with high-dimensional microarray data. In this paper, the classification procedure consisting of PLS dimension reduction and linear discriminant analysis on the new components is compared with some of the best state-of-the-art classification methods. Moreover, a boosting algorithm is applied to this classification method. In addition, a simple procedure to choose the number of PLS components is suggested. The connection between PLS dimension reduction and gene selection is examined and a property of the first PLS component for binary classification is proved. In addition, we show how PLS can be used for data visualization using real data. The whole study is based on 9 real microarray cancer data sets.
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Khan, J., Wei, J. S., Ringnér, M., Saal, L. H., Ladanyi, M., Westermann, F., Berthold, F., Schwab, M., Antonescu, C. R., Peterson, C., et al. (2001) · Nature Medicine · doi:10.1038/89044 · Cited by 2,644
SIMPLS: An alternative approach to partial least squares regression
de Jong, S. (1993) · Chemometrics and Intelligent Laboratory Systems · doi:10.1016/0169-7439(93)85002-x · Cited by 1,905 · cited 2×
“In this paper, we use the SIMPLS algorithm by de Jong (1993), which can be seen as a generalization for multicategorical response variables of the algorithm used by Nguyen and Rocke (2002).”
Boosting a Weak Learning Algorithm by Majority
Freund, Y. (1995) · Information and Computation · doi:10.1006/inco.1995.1136 · Cited by 1,674
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Rohart, F., Gautier, B., Singh, A., & Lê Cao, K.-A. (2017) · PLOS Computational Biology · doi:10.1371/journal.pcbi.1005752 · Cited by 4,056
Partial least squares: a versatile tool for the analysis of high-dimensional genomic data
Boulesteix, A.-L., & Strimmer, K. (2006) · Briefings in Bioinformatics · doi:10.1093/bib/bbl016 · Cited by 802
Self-citationHuman–Agent Teaming for Multirobot Control: A Review of Human Factors Issues
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Weighted k-Nearest-Neighbor Techniques and Ordinal Classification
Hechenbichler, K., & Schliep, K. P. (2004) · Econstor (Econstor) · doi:10.5282/ubm/epub.1769 · Cited by 307
Metadata
- Authors
- Boulesteix, A.-L.
- Venue
- Statistical Applications in Genetics and Molecular Biology
- Publisher
- Walter de Gruyter GmbH
- Published
- 2004-01-23
- Volume
- 3
- Issue
- 1
- Pages
- 1-30
- ISSN
- 1544-6115 (ISSN-L)
- OpenAlex
- W2015961513
- Cited by
- 210
- References
- 3
- FWCI
- 2.84
- Type
- journal article
- Language
- en
- Open access
- green
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