Variable Selection in Discriminant Partial Least-Squares Analysis

Alsberg, Bjørn K.; Kell, Douglas B.; Goodacre, Royston

doi:10.1021/ac980506o

Cited by 111 publications

(65 citation statements)

References 57 publications

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“…It optimizes the fitting and prediction to {-1/1}-coded membershipindicating variables in the development of latent variables. 21,22 The classifying performance of PLS-DA is improved by means of MWPLS-DA, which employs the algorithm of moving window partial least aquares regression (MWPLSR) to select the discriminating region from the whole region.…”

Section: Algorithmmentioning

confidence: 99%

Rapid Classification of Turmeric Based on DNA Fingerprint by Near-Infrared Spectroscopy Combined with Moving Window Partial Least Squares-Discrimination Analysis

2017

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In this research, near-infrared (NIR) spectroscopy in combination with moving window partial least squares-discrimination analysis (MWPLS-DA) was utilized to discriminate the variety of turmeric based on DNA markers, which correlated to the quantity of curcuminoid. Curcuminoid was used as a marker compound in variety identification due to the most pharmacological properties of turmeric possessed from it. MWPLS-DA optimized informative NIR spectral regions for the fitting and prediction to {-1/1}-coded turmeric varieties, indicating variables in the development of latent variables in discrimination analysis. Consequently, MWPLS-DA benefited in the selection of combined informative NIR spectral regions of 1100 -1260, 1300 -1500 and 1880 -2500 nm for classification modeling of turmeric variety with 148 calibration samples, and yielded the results better than that obtained from a partial least squares-discrimination analysis (PLS-DA) model built by using the whole NIR spectral region. An effective and rapid strategy of using NIR in combination with MWPLS-DA provided the best variety identification results of 100% in both specificity and total accuracy for 48 test samples.

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Section: Algorithmmentioning

confidence: 99%

Rapid Classification of Turmeric Based on DNA Fingerprint by Near-Infrared Spectroscopy Combined with Moving Window Partial Least Squares-Discrimination Analysis

2017

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“…Partial least-squares discriminant analysis (PLSDA) 21,22 is a linear-regression method based on all spectra information. The multivariate variables corresponding to the observations (spectral descriptors) are related to the class membership for each sample.…”

Section: Comparison Of Different Recognition Methods For Identificationmentioning

confidence: 99%

“…Spectral intervals with lower classification errors and less latent variables are then selected and combined to develop a PLSDA model. 14,15 The model can be described as follows:…”

Section: Principle Of Moving Window Partial Least-squares Discriminanmentioning

confidence: 99%

Construction of an Efficacious Model for a Nondestructive Identification of Traditional Chinese Medicines Liuwei Dihuang Pills from Different Manufacturers Using Near-infrared Spectroscopy and Moving Window Partial Least-squares Discriminant Analysis

Huan

et al. 2009

ANAL. SCI.

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This paper reports on the construction of an efficacious model for a non-invasive identification of traditional Chinese medicines, Liuwei Dihuang pills from different manufacturers, on the basis of near-infrared spectra (NIRS) coupled with moving window partial least-squares discriminant analysis (MWPLSDA). Considering the continuity of near-infrared spectral measurements, MWPLSDA is used to identify continuous and highly classification-related information intervals, a simple, yet effective classification model that can be developed for identifying accurate 150 Liuwei Dihuang pills from five different manufacturers. Meanwhile, the method is compared with some traditional pattern-recognition methods including principal component analysis (PCA), linear discriminant analysis (LDA) and partial least-squares discriminant analysis (PLSDA). The obtained results show that the method not only can reduce the operation time, but also significantly improves the classification accuracy. Hence, the nondestructive method can be expected to be promising for more practical applications on quality control and the discrimination of traditional Chinese medicine.

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“…In these models, the measured oocyte PI values for each fish served as reference values. To determine how robust a PLSR model is, the number of latent variables, correlation coefficient (R), standard error and outlier diagnostics need to be determined [17]. After a PLSR calibration model is established, it is validated by cross validation using plasma samples from either 9 the same data set that were not used for model construction or with plasma samples 180 from new data sets.…”

Section: Spectral Processing and Chemometricsmentioning

confidence: 99%

Determining Ovarian Maturity in Farmed Sturgeon 1 (Acipenser transmontanus) for Caviar Production Using Fourier Transform Infrared Spectroscopy (FT-IR)

JPV¹

2014

J Aquac Res Development

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Ovarian maturity of white sturgeon (Acipenser transmontanus, Acipenseridae) farmed in California (Sterling Caviar, LLC) (N=400) and Idaho (Fish Breeders and Blind Canyon Aqua Ranch) (N=143) was determined by correlating blood plasma spectral features [(Fourier transform infrared (FT-IR, 4000-400 cm -1 ) spectroscopy] with oocyte polarization index (PI), an index of germinal vesicle migration. A total of ~20,000 spectra were collected over a period of four years (2007, 2008, 2009 and 2010). Mathematical models could predict maturity in fish at a later year of harvest (i.e., 2010) and at either the California or Idaho production sites. PI values of 0.10, 0.15, and 0.20 were selected for segregating fish into subgroups based on ovarian maturity. Spectral features for specific proteins, lipids, carbohydrates and nucleic acids were related to fish maturity stages. Mathematical models could predict the actual PI values based on plasma spectral features in fish from 2010 based on models developed and validated from fish harvested in [2007][2008][2009]. These models worked equally well whether the fish were raised in California or Idaho. This research indicates that infrared spectroscopy provides a rapid and less invasive method to segregate sturgeon females according to maturity levels and has the potential to substitute for the traditional surgical biopsy to determine stage of maturity.

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Variable Selection in Discriminant Partial Least-Squares Analysis

Cited by 111 publications

References 57 publications

Rapid Classification of Turmeric Based on DNA Fingerprint by Near-Infrared Spectroscopy Combined with Moving Window Partial Least Squares-Discrimination Analysis

Rapid Classification of Turmeric Based on DNA Fingerprint by Near-Infrared Spectroscopy Combined with Moving Window Partial Least Squares-Discrimination Analysis

Construction of an Efficacious Model for a Nondestructive Identification of Traditional Chinese Medicines Liuwei Dihuang Pills from Different Manufacturers Using Near-infrared Spectroscopy and Moving Window Partial Least-squares Discriminant Analysis

Determining Ovarian Maturity in Farmed Sturgeon 1 (Acipenser transmontanus) for Caviar Production Using Fourier Transform Infrared Spectroscopy (FT-IR)

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