Feature selection algorithm based on PDF/PMF area difference; Biomedical Signal Processing and Control; Vol. 57

Feature selection algorithm based on PDF/PMF area difference; Biomedical Signal Processing and Control; Vol. 57

Detalhes bibliográficos
Parent link:	Biomedical Signal Processing and Control Vol. 57.— 2020.— [101681, 15 p.]
Autor Corporativo:	Национальный исследовательский Томский политехнический университет Управление проректора по научной работе и инновациям Центр RASA в Томске Лаборатория дизайна медицинских изделий
Outros Autores:	Danilov V. V. Vyacheslav Vladimirovich, Skirnevsky I. P. Igor Petrovich, Manakov R. Roman, Gerget O. M. Olga Mikhailovna, Milgani F.
Resumo:	Title screen The research devoted to feature selection has been studied extensively in the last years and as a result, important results have been obtained. However, a feature selection technique remains a complex problem because of the necessity for its outcomes to be reliable and accurate within different limitations. Nowadays, there is no feature selection algorithm that outperforms any others. Our research is focused on the development of a feature selection algorithm and its comparison with other well-known feature selection techniques. The proposed algorithm is used for searching for the most reliable features. Despite the fact that we used the proposed algorithm in a specific case in our study (catheter detection task), the algorithm can also be used for general purposes as well. Therefore, it can be easily scaled to find the relevant features of the region of interest in other tasks. Режим доступа: по договору с организацией-держателем ресурса
Idioma:	inglês
Publicado em:	2020
Assuntos:	электронный ресурс труды учёных ТПУ feature selection feature engineering segmentation catheter detection SVM machine learning функции сегментация машинное обучение
Acesso em linha:	https://doi.org/10.1016/j.bspc.2019.101681
Formato:	Recurso Electrónico Capítulo de Livro
KOHA link:	https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=662752

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