Comparison of species classification models of mass spectrometry data: Kernel discriminant analysis vs Random forest; a case study of Afrormosia (<EM>Pericopsis elata</EM> (Harms) Meeuwen)

Deklerck, V.; Finch, K.; Gasson, P.; Van den Bulcke, J.; Van Acker, J.; Beeckman, H.; Espinoza, E.

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Authors

Deklerck, V.

Finch, K.

Gasson, P.

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Discipline

Biological sciences

Agriculture, Forestry and Fisheries

Subject

Wood biology

Audience

Scientific

Date

2017

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Citation

Deklerck, V.; Finch, K.; Gasson, P.; Van den Bulcke, J.; Van Acker, J.; Beeckman, H.; Espinoza, E. (2017). Comparison of species classification models of mass spectrometry data: Kernel discriminant analysis vs Random forest; a case study of Afrormosia (Pericopsis elata (Harms) Meeuwen). , Rapid Communications in Mass Spectrometry, Vol. 31(19), 1582-1588, DOI: 10.1002/rcm.7939.

Identifiers

uri: https://orfeo.belnet.be/handle/internal/11962

doi: http://dx.doi.org/10.1002/rcm.7939

Type

Article

Peer-Review

Yes

Language

eng

Comparison of species classification models of mass spectrometry data: Kernel discriminant analysis vs Random forest; a case study of Afrormosia (Pericopsis elata (Harms) Meeuwen)