A. Karmenyan, D. Vrazhnov, E. Sandykova, E. Perevedentseva, A. Krivokharchenko, V. Nadtochenko, Chia-Liang Cheng, T. Kabanova, Tatyana E. Malakhova
{"title":"拉曼微光谱数据信息特征选择方法","authors":"A. Karmenyan, D. Vrazhnov, E. Sandykova, E. Perevedentseva, A. Krivokharchenko, V. Nadtochenko, Chia-Liang Cheng, T. Kabanova, Tatyana E. Malakhova","doi":"10.1117/12.2613966","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":205170,"journal":{"name":"Atomic and Molecular Pulsed Lasers","volume":"64 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Informative feature selection method for Raman micro-spectroscopy data\",\"authors\":\"A. Karmenyan, D. Vrazhnov, E. Sandykova, E. Perevedentseva, A. Krivokharchenko, V. Nadtochenko, Chia-Liang Cheng, T. Kabanova, Tatyana E. Malakhova\",\"doi\":\"10.1117/12.2613966\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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.\",\"PeriodicalId\":205170,\"journal\":{\"name\":\"Atomic and Molecular Pulsed Lasers\",\"volume\":\"64 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-12-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Atomic and Molecular Pulsed Lasers\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1117/12.2613966\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Atomic and Molecular Pulsed Lasers","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1117/12.2613966","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Informative feature selection method for Raman micro-spectroscopy data
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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