A New Validation Criterion for Guiding the Selection of Variables by the Successive Projections Algorithm in Classification Problems

Soares, Sófacles Figueredo Carreiro; Galvão, Roberto Kawakami Harrop; Pontes, Márcio José Coelho; Araújo, Mário César Ugulino de

doi:10.5935/0103-5053.20130262

Cited by 2 publications

(2 citation statements)

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“…Since the number of samples is small and does not favor the construction of a validation set, SPA–LDA was used with internal validation (the training set was used to select the lowest risk of incorrect classification). 42,43 In order to avoid overfitting in the classification models, the maximum number of variables (N) equal to eight (number of samples from the lowest Training class minus the number of classes for modeling) was selected.…”

Section: Methodsmentioning

confidence: 99%

A fast and low-cost approach to quality control of alcohol-based hand sanitizer using a portable near infrared spectrometer and chemometrics

Silva

Ribeiro

Vidal

et al. 2021

Journal of Near Infrared Spectroscopy

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The use of alcohol-based hand sanitizers is recommended as one of several strategies to minimize contamination and spread of the COVID-19 disease. Current reports suggest that the virucidal potential of ethanol occurs at concentrations close to 70%. Traditional methods of verifying the ethanol concentration in such products invite potential errors due to the viscosity of chemical components or may be prohibitively expensive to undertake in large demand. Near infrared (NIR) spectroscopy and chemometrics have already been used for the determination of ethanol in other matrices and present an alternative fast and reliable approach to quality control of alcohol-based hand sanitizers. In this study, a portable NIR spectrometer combined with classification chemometric tools, i.e., partial least square discriminant analysis (PLS–DA) and linear discriminant analysis with successive algorithm projection (SPA–LDA) were used to construct models to identify conforming and non-conforming commercial and laboratory synthesized hand sanitizer samples. Principal component analysis (PCA) was applied in an exploratory data study. Three principal components accounted for 99% of data variance and demonstrate clustering of conforming and non-conforming samples. The PLS–DA and SPA–LDA classification models presented 77 and 100% of accuracy in cross/internal validation respectively and 100% of accuracy in the classification of test samples. A total of 43% commercial samples evaluated using the PLS–DA and SPA–LDA presented ethanol content non-conforming for hand sanitizer gel. These results indicate that use of NIR spectroscopy and chemometrics is a promising strategy, yielding a method that is fast, portable, and reliable for discrimination of alcohol-based hand sanitizers with respect to conforming and non-conforming ethanol concentrations.

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Section: Methodsmentioning

confidence: 99%

A fast and low-cost approach to quality control of alcohol-based hand sanitizer using a portable near infrared spectrometer and chemometrics

Silva

Ribeiro

Vidal

et al. 2021

Journal of Near Infrared Spectroscopy

View full text Add to dashboard Cite

show abstract

“…However, SPA has two disadvantages: (1) If the sample size of the calibration set is small, the samples for modeling are unrepresentative. Although the variable collinearity of the calibration set is minimized, on the validation set, an inappropriate selection of variables could mean that the prediction results are not satisfactory [ 22 , 23 , 24 ]. (2) SPA is an unsupervised variable selection method, therefore, the selected variables do not necessarily reflect the information of the measured component well [ 25 , 26 ].…”

Section: Introductionmentioning

confidence: 99%

An Ensemble Successive Project Algorithm for Liquor Detection Using Near Infrared Sensor

Ren

Wang

et al. 2016

Sensors

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Spectral analysis technique based on near infrared (NIR) sensor is a powerful tool for complex information processing and high precision recognition, and it has been widely applied to quality analysis and online inspection of agricultural products. This paper proposes a new method to address the instability of small sample sizes in the successive projections algorithm (SPA) as well as the lack of association between selected variables and the analyte. The proposed method is an evaluated bootstrap ensemble SPA method (EBSPA) based on a variable evaluation index (EI) for variable selection, and is applied to the quantitative prediction of alcohol concentrations in liquor using NIR sensor. In the experiment, the proposed EBSPA with three kinds of modeling methods are established to test their performance. In addition, the proposed EBSPA combined with partial least square is compared with other state-of-the-art variable selection methods. The results show that the proposed method can solve the defects of SPA and it has the best generalization performance and stability. Furthermore, the physical meaning of the selected variables from the near infrared sensor data is clear, which can effectively reduce the variables and improve their prediction accuracy.

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A New Validation Criterion for Guiding the Selection of Variables by the Successive Projections Algorithm in Classification Problems

Cited by 2 publications

References 1 publication

A fast and low-cost approach to quality control of alcohol-based hand sanitizer using a portable near infrared spectrometer and chemometrics

A fast and low-cost approach to quality control of alcohol-based hand sanitizer using a portable near infrared spectrometer and chemometrics

An Ensemble Successive Project Algorithm for Liquor Detection Using Near Infrared Sensor

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