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dc.contributor.author
Melo Milanez, Karla Danielle Tavares de
dc.contributor.author
Nóbrega, Thiago César Araújo
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Silva Do Nascimento, Danielle
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dc.contributor.author
Galvão, Roberto Kawakami Harrop
dc.contributor.author
Pontes, Márcio José Coelho
dc.date.available
2018-08-22T17:16:07Z
dc.date.issued
2017-09-01
dc.identifier.citation
Melo Milanez, Karla Danielle Tavares de; Nóbrega, Thiago César Araújo ; Silva Do Nascimento, Danielle; Galvão, Roberto Kawakami Harrop; Pontes, Márcio José Coelho; Selection of robust variables for transfer of classification models employing the successive projections algorithm; Elsevier Science; Analytica Chimica Acta; 984; 1-9-2017; 76-85
dc.identifier.issn
0003-2670
dc.identifier.uri
http://hdl.handle.net/11336/56597
dc.description.abstract
Multivariate models have been widely used in analytical problems involving quantitative and qualitative analyzes. However, there are cases in which a model is not applicable to spectra of samples obtained under new experimental conditions or in an instrument not involved in the modeling step. A solution to this problem is the transfer of multivariate models, usually performed using standardization of the spectral responses or enhancement of the robustness of the model. This present paper proposes two new criteria for selection of robust variables for classification transfer employing the successive projections algorithm (SPA). These variables are then used to build models based on linear discriminant analysis (LDA) with low sensitivity with respect to the differences between the responses of the instruments involved. For this purpose, transfer samples are included in the calculation of the cost for each subset of variables under consideration. The proposed methods are evaluated for two case studies involving identification of adulteration of extra virgin olive oil (EVOO) and hydrated ethyl alcohol fuel (HEAF) using UV–Vis and NIR spectroscopy, respectively. In both cases, similar or better classification transfer results (obtained for a test set measured on the secondary instrument) employing the two criteria were obtained in comparison with direct standardization (DS) and piecewise direct standardization (PDS). For the UV–Vis data, both proposed criteria achieved the correct classification rate (CCR) of 85%, while the best CCR obtained for the standardization methods was 81% for DS. For the NIR data, 92.5% of CCR was obtained by both criteria as well as DS. The results demonstrated the possibility of using either of the criteria proposed for building robust models as an alternative to the standardization of spectral responses for transfer of classification.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
Elsevier Science
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dc.rights
info:eu-repo/semantics/openAccess
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.subject
Multivariate Classification Transfer
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Nir Spectroscopy
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Robust Modeling
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Standardization Methods
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Successive Projections Algorithm
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Uv–Ndash;Vis Spectroscopy
dc.subject.classification
Otras Ciencias Químicas
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dc.subject.classification
Ciencias Químicas
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dc.subject.classification
CIENCIAS NATURALES Y EXACTAS
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dc.title
Selection of robust variables for transfer of classification models employing the successive projections algorithm
dc.type
info:eu-repo/semantics/article
dc.type
info:ar-repo/semantics/artículo
dc.type
info:eu-repo/semantics/publishedVersion
dc.date.updated
2018-08-21T13:04:10Z
dc.journal.volume
984
dc.journal.pagination
76-85
dc.journal.pais
Países Bajos
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dc.journal.ciudad
Amsterdam
dc.description.fil
Fil: Melo Milanez, Karla Danielle Tavares de. Universidade Federal da Paraíba; Brasil
dc.description.fil
Fil: Nóbrega, Thiago César Araújo. Universidade Federal da Paraíba; Brasil
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Fil: Silva Do Nascimento, Danielle. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Química del Sur. Universidad Nacional del Sur. Departamento de Química. Instituto de Química del Sur; Argentina
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Fil: Galvão, Roberto Kawakami Harrop. Instituto Tecnológico de Aeronáutica; Brasil
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Fil: Pontes, Márcio José Coelho. Universidade Federal da Paraíba; Brasil
dc.journal.title
Analytica Chimica Acta
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dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S0003267017308413
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1016/j.aca.2017.07.037
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