کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
430021 687781 2014 17 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
A feature construction approach for genetic iterative rule learning algorithm
ترجمه فارسی عنوان
یک روش ساختاری ویژگی برای الگوریتم یادگیری قوانین تکرار ژنتیکی
کلمات کلیدی
سیستم های فازی ژنتیکی، ساخت و ساز ویژگی ها، رویکرد یادگیری خیالی، طبقه بندی
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نظریه محاسباتی و ریاضیات
چکیده انگلیسی


• A method to include feature construction in a fuzzy rule learning algorithm is proposed.
• The feature construction incorporates relations and functions in the antecedent of fuzzy rules.
• This procedure allows to increase the amount of information extracted from the initial variables.
• The proposal NSLV-FR obtains results with a good balance among accuracy, interpretability and time needed to get the model.

This paper presents a proposal that introduces the use of feature construction in a fuzzy rule learning algorithm. This is done by means of the combination of two different approaches together with a new learning strategy. The first of these two approaches consists of using relations in the antecedent of fuzzy rules while the second one employs functions in the antecedent of that rules. Thus, the method we propose tries to integrate these two models so that, using a learning strategy that allows us to start learning more general rules and finish the process learning more specific ones, we are able to increase the amount of information extracted from the initial variables. The experimental results show that the proposed method obtains a good trade-off among accuracy, interpretability and time needed to get the model in relation to the rest of algorithms using feature construction involved in the comparison.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Computer and System Sciences - Volume 80, Issue 1, February 2014, Pages 101–117
نویسندگان
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