کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
10755569 | 1050376 | 2014 | 7 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Robust and stable feature selection by integrating ranking methods and wrapper technique in genetic data classification
ترجمه فارسی عنوان
انتخاب قوی و پایدار با استفاده از یکپارچه سازی روش های رتبه بندی و تکنیک بسته بندی در طبقه بندی داده های ژنتیکی
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کلمات کلیدی
موضوعات مرتبط
علوم زیستی و بیوفناوری
بیوشیمی، ژنتیک و زیست شناسی مولکولی
زیست شیمی
چکیده انگلیسی
High dimensional data increase the dimension of space and consequently the computational complexity and result in lower generalization. From these types of classification problems microarray data classification can be mentioned. Microarrays contain genetic and biological data which can be used to diagnose diseases including various types of cancers and tumors. Having intractable dimensions, dimension reduction process is necessary on these data. The main goal of this paper is to provide a method for dimension reduction and classification of genetic data sets. The proposed approach includes different stages. In the first stage, several feature ranking methods are fused for enhancing the robustness and stability of feature selection process. Wrapper method is combined with the proposed hybrid ranking method to embed the interaction between genes. Afterwards, the classification process is applied using support vector machine. Before feeding the data to the SVM classifier the problem of imbalance classes of data in the training phase should be overcame. The experimental results of the proposed approach on five microarray databases show that the robustness metric of the feature selection process is in the interval of [0.70, 0.88]. Also the classification accuracy is in the range of [91%, 96%].
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Biochemical and Biophysical Research Communications - Volume 446, Issue 4, 18 April 2014, Pages 850-856
Journal: Biochemical and Biophysical Research Communications - Volume 446, Issue 4, 18 April 2014, Pages 850-856
نویسندگان
Maryam Yassi, Mohammad Hossein Moattar,