کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
531157 869814 2006 12 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Selecting features in microarray classification using ROC curves
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر چشم انداز کامپیوتر و تشخیص الگو
پیش نمایش صفحه اول مقاله
Selecting features in microarray classification using ROC curves
چکیده انگلیسی

We present a new method based on the ROC (Receiver Operating Characteristic) curve to efficiently select a feature subset in classifying a high-dimensional microarray dataset with a limited number of observations. Our method has two steps: (1) selecting the most relevant features to the target label using the ROC curve and (2) iteratively eliminating a redundant feature using the ROC curves. The ROC curve is strongly related with a non-parametric hypothesis testing, which must be effective for a dataset with small numerical observations. Experiments with real datasets revealed the significant performance advantage of our method over two competing feature subset selection methods.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Pattern Recognition - Volume 39, Issue 12, December 2006, Pages 2393–2404
نویسندگان
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