کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
412504 | 679647 | 2012 | 8 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Biomarker discovery using 1-norm regularization for multiclass earthworm microarray gene expression data
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
Novel biomarkers can be discovered through mining high dimensional microarray datasets using machine learning techniques. Here we propose a novel recursive gene selection method which can handle the multiclass setting effectively and efficiently. The selection is performed iteratively. In each iteration, a linear multiclass classifier is trained using 1-norm regularization, which leads to sparse weight vectors, i.e., many feature weights are exactly zero. Those zero-weight features are eliminated in the next iteration. The empirical results demonstrate that the selected features (genes) have very competitive discriminative power. In addition, the selection process has fast rate of convergence.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Neurocomputing - Volume 92, 1 September 2012, Pages 36–43
Journal: Neurocomputing - Volume 92, 1 September 2012, Pages 36–43
نویسندگان
Xiaofei Nan, Nan Wang, Ping Gong, Chaoyang Zhang, Yixin Chen, Dawn Wilkins,