کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
388813 660941 2009 5 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
A sequential feature extraction approach for naïve bayes classification of microarray data
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
A sequential feature extraction approach for naïve bayes classification of microarray data
چکیده انگلیسی

Accurate classification of microarray data plays a vital role in cancer prediction and diagnosis. Previous studies have demonstrated the usefulness of naïve Bayes classifier in solving various classification problems. In microarray data analysis, however, the conditional independence assumption embedded in the classifier itself and the characteristics of microarray data, e.g. the extremely high dimensionality, may severely affect the classification performance of naïve Bayes classifier. This paper presents a sequential feature extraction approach for naïve Bayes classification of microarray data. The proposed approach consists of feature selection by stepwise regression and feature transformation by class-conditional independent component analysis. Experimental results on five microarray datasets demonstrate the effectiveness of the proposed approach in improving the performance of naïve Bayes classifier in microarray data analysis.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Expert Systems with Applications - Volume 36, Issue 6, August 2009, Pages 9919–9923
نویسندگان
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