کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6857733 | 664769 | 2014 | 25 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
A review of microarray datasets and applied feature selection methods
ترجمه فارسی عنوان
بررسی مجموعه داده های میکروارا و روش های انتخاب ویژگی های کاربردی
دانلود مقاله + سفارش ترجمه
دانلود مقاله ISI انگلیسی
رایگان برای ایرانیان
کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
چکیده انگلیسی
Microarray data classification is a difficult challenge for machine learning researchers due to its high number of features and the small sample sizes. Feature selection has been soon considered a de facto standard in this field since its introduction, and a huge number of feature selection methods were utilized trying to reduce the input dimensionality while improving the classification performance. This paper is devoted to reviewing the most up-to-date feature selection methods developed in this field and the microarray databases most frequently used in the literature. We also make the interested reader aware of the problematic of data characteristics in this domain, such as the imbalance of the data, their complexity, or the so-called dataset shift. Finally, an experimental evaluation on the most representative datasets using well-known feature selection methods is presented, bearing in mind that the aim is not to provide the best feature selection method, but to facilitate their comparative study by the research community.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Information Sciences - Volume 282, 20 October 2014, Pages 111-135
Journal: Information Sciences - Volume 282, 20 October 2014, Pages 111-135
نویسندگان
V. Bolón-Canedo, N. Sánchez-Maroño, A. Alonso-Betanzos, J.M. BenÃtez, F. Herrera,