کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
505566 | 864519 | 2010 | 7 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Decision forest for classification of gene expression data
دانلود مقاله + سفارش ترجمه
دانلود مقاله ISI انگلیسی
رایگان برای ایرانیان
کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
نرم افزارهای علوم کامپیوتر
پیش نمایش صفحه اول مقاله

چکیده انگلیسی
This study attempts to propose an improved decision forest (IDF) with an integrated graphical user interface. Based on four gene expression data sets, the IDF not only outperforms the original decision forest, but also is superior or comparable to other state-of-the-art machine learning methods, especially in dealing with high dimensional data. With an integrated built-in feature selection (FS) mechanism and fewer parameters to tune, it can be trained more efficiently than methods such as support vector machine, and can be built with much fewer trees than other popular tree-based ensemble methods. Moreover, it suffers less from the curse of dimensionality.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computers in Biology and Medicine - Volume 40, Issue 8, August 2010, Pages 698–704
Journal: Computers in Biology and Medicine - Volume 40, Issue 8, August 2010, Pages 698–704
نویسندگان
Jianping Huang, Hong Fang, Xiaohui Fan,