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nipals, rcga and ls-svm implementation  (MathWorks Inc)


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    MathWorks Inc nipals, rcga and ls-svm implementation
    Nipals, Rcga And Ls Svm Implementation, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/ls-svm+system/10__1016_slash_j__jfca__2024__106543-132-1-16
    Average 90 stars, based on 1 article reviews
    nipals, rcga and ls-svm implementation - by Bioz Stars, 2026-09
    90/100 stars

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    other:

    Article Title: Optimizing the selection of natural fibre reinforcement and polymer matrix for plastic composite using LS-SVM technique.
    Article Snippet: • Surveyed natural fibre and polymer combinations for PMC production.. • Suggested a LSO for natural fibre selection with the best proportions.. • Local search optimization uses a basic multi-class SVM as an objective function.



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    Image Search Results


    Journal: STAR Protocols

    Article Title: Protocol for state-of-health prediction of lithium-ion batteries based on machine learning

    doi: 10.1016/j.xpro.2022.101272

    Figure Lengend Snippet:

    Article Snippet: LS-SVM MATLAB script package , ( ) , https://www.esat.kuleuven.be/sista/lssvmlab/.

    Techniques: Battery, Software

    Selected applications of NIR-hyperspectral imaging in agriculturally important seeds (reflectance mode).

    Journal: Sensors (Basel, Switzerland)

    Article Title: Near-Infrared Hyperspectral Imaging Pipelines for Pasture Seed Quality Evaluation: An Overview

    doi: 10.3390/s22051981

    Figure Lengend Snippet: Selected applications of NIR-hyperspectral imaging in agriculturally important seeds (reflectance mode).

    Article Snippet: Maize seed varietal classification (n = 1632) , PCA; LS-SVM , 400–1000 nm , Wavelength selections: multi-linear discriminant analysis (MLDA) vs. UVE and SPA , ENVI 4.3 , MATLAB 2009b (LS-SVM toolbox) , Full wavelength: calibration of 100% and prediction of 93.26%. Wavelengths, 5–15 selected: MLDA calibration of 99.39–99.88% and prediction of 90.40–93.81%; UVE calibration of 99.46–99.85% and prediction of 88.20–91.94%; SPA: calibration of 98.66–99.40% and prediction of 80.8–87.40% , [ ] .

    Techniques: Imaging, Selection, Software, Plasmid Preparation