کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
1136023 956155 2006 11 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Genetic algorithm in designing fuzzy information retrieval-based classifier by principal component analysis
موضوعات مرتبط
مهندسی و علوم پایه سایر رشته های مهندسی مهندسی صنعتی و تولید
پیش نمایش صفحه اول مقاله
Genetic algorithm in designing fuzzy information retrieval-based classifier by principal component analysis
چکیده انگلیسی

The aim of this paper is to develop a fuzzy classifier form the point of view of a fuzzy information retrieval system. The genetic algorithm is employed to find useful fuzzy concepts with high classification performance for classification problems; then, each of classes and patterns can be represented by a fuzzy set of useful fuzzy concepts. Each of fuzzy concepts is linguistically interpreted and the corresponding membership functions remain fixed during the evolution. A pattern can be categorized into one class if there exists a maximum degree of similarity between them. For not distorting the usefulness of the proposed classifier for high-dimensional problems, the principal component analysis is incorporated into the proposed classifier to reduce dimensions. The generalization ability of the proposed classifier is examined by performing computer simulations on some well-known data sets, such as the breast cancer data and the wine classification data. The results demonstrate that the proposed classifier works well in comparison with other classification methods.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computers & Industrial Engineering - Volume 51, Issue 1, September 2006, Pages 117–127
نویسندگان
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