Improving detection of apneic events by learning from examples and treatment of missing data / دانلود فایل

مشخصات کلی Improving detection of apneic events by learning from examples and treatment of missing data

نویسنده کتاب (Author):

Hernández Pereira, Elena; Álvarez Estévez, Diego; Moret Bonillo, Vicente

انتشارات (Publisher):

I O S Press 2014

ویرایش و نوع فایل (Edition/Format):

 Downloadable article : English

منبع (Database):

WorldCat

عنوان ژورنال (Publication):

elena-hernandez-pereira-diego-alvarez-estevez-vicente-moret-bonillo-improving-detection-of-apneic-events-by-learning-from-examples-and-treatment-of-missing-data-studies-in-health

موضوع (Subject):

Respiratory pattern classification       Machine learning       Algorithms       View all subjects      

توضیحات خلاصه (Summary):

[Abstract] This paper presents a comparative study over the respiratory pattern classification task involving three missing data imputation techniques, and four different machine learning algorithms. The main goal was to find a classifier that achieves the best accuracy results using a scalable imputation method in comparison to the method used in a previous work of the authors. The results obtained show that the Self-organization maps imputation method allows any classifier to achieve improvements over the rest of the imputation methods, and that the Feedforward neural network classifier offers the best performance regardless the imputation method used.  Read more…

ژانر / فرم:info:eu-repo/semantics/article

موضوع:Internet resource

نوع منبع:Internet Resource, Article

تمام نویسندگان / همکاران: Hernández Pereira, Elena; Álvarez Estévez, Diego; Moret Bonillo, Vicente

شناسه OCLC:979265395

Language Note:English

فهرست محتوا:0926-9630 1879-8365 http://hdl.handle.net/2183/18135 10.3233/978-1-61499-474-9-213