کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
388588 | 660930 | 2007 | 12 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
A hybrid approach for feature subset selection using neural networks and ant colony optimization
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: A hybrid approach for feature subset selection using neural networks and ant colony optimization A hybrid approach for feature subset selection using neural networks and ant colony optimization](/preview/png/388588.png)
چکیده انگلیسی
One of the significant research problems in multivariate analysis is the selection of a subset of input variables that can predict the desired output with an acceptable level of accuracy. This goal is attained through the elimination of the variables that produce noise or, are strictly correlated with other already selected variables. Feature subset selection (selection of the input variables) is important in correlation analysis and in the field of classification and modeling. This paper presents a hybrid method based on ant colony optimization and artificial neural networks (ANNs) to address feature selection. The proposed hybrid model is demonstrated using data sets from the domain of medical diagnosis, yielding promising results.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Expert Systems with Applications - Volume 33, Issue 1, July 2007, Pages 49–60
Journal: Expert Systems with Applications - Volume 33, Issue 1, July 2007, Pages 49–60
نویسندگان
Rahul Karthik Sivagaminathan, Sreeram Ramakrishnan,