title: Combination of the Manifold Dimensionality Reduction Methods with Least Squares Support vector machines for Classifying the Species of Sorghum Seeds.
abstract: This study was carried out for rapid and noninvasive determination of the class of sorghum species by using the manifold dimensionality reduction (MDR) method and the nonlinear regression method of least squares support vector machines (LS-SVM) combing with the mid-infrared spectroscopy (MIRS) techniques. The methods of Durbin and Run test of augmented partial residual plot (APaRP) were performed to diagnose the nonlinearity of the raw spectral data. The nonlinear MDR methods of isometric feature mapping (ISOMAP), local linear embedding, laplacian eigenmaps and local tangent space alignment, as well as the linear MDR methods of principle component analysis and metric multidimensional scaling were employed to extract the feature variables. The extracted characteristic variables were utilized as the input of LS-SVM and established the relationship between the spectra and the target attributes. The mean average precision (MAP) scores and prediction accuracy were respectively used to evaluate the performance of models. The prediction results showed that the ISOMAP-LS-SVM model obtained the best classification performance, where the MAP scores and prediction accuracy were 0.947 and 92.86%, respectively. It can be concluded that the ISOMAP-LS-SVM model combined with the MIRS technique has the potential of classifying the species of sorghum in a reasonable accuracy.
authors.affiliation: College of Electrical Engineering, Yancheng Institute of Technology, No.1 Middle Road Hope Avenue, Yancheng, Jiangsu Province 224051, P.R. China.
authors.forename: Y M
authors.initials: YM
authors.lastname: Chen
authors.affiliation: College of Electrical Engineering, Yancheng Institute of Technology, No.1 Middle Road Hope Avenue, Yancheng, Jiangsu Province 224051, P.R. China.
authors.forename: P
authors.initials: P
authors.lastname: Lin
authors.affiliation: College of Electrical Engineering, Yancheng Institute of Technology, No.1 Middle Road Hope Avenue, Yancheng, Jiangsu Province 224051, P.R. China.
authors.forename: J Q
authors.initials: JQ
authors.lastname: He
authors.affiliation: College of Biosystems Engineering and Food Science, Zhejiang University, 866 Yuhangtang Road, Hangzhou 310058, China.
authors.forename: Y
authors.initials: Y
authors.lastname: He
authors.affiliation: College of Biosystems Engineering and Food Science, Zhejiang University, 866 Yuhangtang Road, Hangzhou 310058, China.
authors.forename: X L
authors.initials: XL
authors.lastname: Li
mesh_terms: D000465:Algorithms; D016018:Least-Squares Analysis; D012639:Seeds / Q000145:classification*; D045868:Sorghum; D060388:Support Vector Machine
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