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Mathematical optimization methods for the analysis of compositional data: subset selection, unmixing and prediction

Jan Verwaeren (UGent)
(2014)
Author
Promoter
(UGent)
Organization
Keywords
machine learning, unmixing, subset selection, mathematical optimization, compositional data

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Citation

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MLA
Verwaeren, Jan. Mathematical Optimization Methods for the Analysis of Compositional Data: Subset Selection, Unmixing and Prediction. Ghent University. Faculty of Bioscience Engineering, 2014.
APA
Verwaeren, J. (2014). Mathematical optimization methods for the analysis of compositional data: subset selection, unmixing and prediction. Ghent University. Faculty of Bioscience Engineering, Ghent, Belgium.
Chicago author-date
Verwaeren, Jan. 2014. “Mathematical Optimization Methods for the Analysis of Compositional Data: Subset Selection, Unmixing and Prediction.” Ghent, Belgium: Ghent University. Faculty of Bioscience Engineering.
Chicago author-date (all authors)
Verwaeren, Jan. 2014. “Mathematical Optimization Methods for the Analysis of Compositional Data: Subset Selection, Unmixing and Prediction.” Ghent, Belgium: Ghent University. Faculty of Bioscience Engineering.
Vancouver
1.
Verwaeren J. Mathematical optimization methods for the analysis of compositional data: subset selection, unmixing and prediction. [Ghent, Belgium]: Ghent University. Faculty of Bioscience Engineering; 2014.
IEEE
[1]
J. Verwaeren, “Mathematical optimization methods for the analysis of compositional data: subset selection, unmixing and prediction,” Ghent University. Faculty of Bioscience Engineering, Ghent, Belgium, 2014.
@phdthesis{4418612,
  author       = {{Verwaeren, Jan}},
  isbn         = {{9789059897113}},
  keywords     = {{machine learning,unmixing,subset selection,mathematical optimization,compositional data}},
  language     = {{eng}},
  pages        = {{XV, 322}},
  publisher    = {{Ghent University. Faculty of Bioscience Engineering}},
  school       = {{Ghent University}},
  title        = {{Mathematical optimization methods for the analysis of compositional data: subset selection, unmixing and prediction}},
  year         = {{2014}},
}