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Informative feature selection method for Raman micro-spectroscopy data A. V. Karmenyan, D. A. Vrazhnov, E. A. Sandykova [et al.]
Material type: ArticleContent type: Текст Media type: электронный Subject(s): рамановская микроспектроскопия | селекция информативных признаков | машинное обучение | ранние эмбрионы млекопитающихGenre/Form: статьи в журналах Online resources: Click here to access online In: Proceedings of SPIE Vol. 12086 : XV International Conference on Pulsed Lasers and Laser Applications, 2021, Tomsk, Russian Federation. P. 120861H-1-120861H-6Abstract: The paper presents an algorithm based on low order statistics for the informative feature extraction for Raman spectroscopy data. The proposed method was tested on mouse preimplantation embryos Raman spectra. Both supervised and unsupervised machine learning methods were applied to selected the most informative features to test the separability of the processed data.No physical items for this record
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The paper presents an algorithm based on low order statistics for the informative feature extraction for Raman spectroscopy data. The proposed method was tested on mouse preimplantation embryos Raman spectra. Both supervised and unsupervised machine learning methods were applied to selected the most informative features to test the separability of the processed data.
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