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دسته بندی:
داده های بزرگ - big data
سال انتشار:
2016
عنوان انگلیسی مقاله:
A First Approach in Evolutionary Fuzzy Systems based on the lateral tuning of the linguistic labels for Big Data classification
ترجمه فارسی عنوان مقاله:
یک رویکرد اول در سیستم های فازی تکاملی بر اساس تنظیم جانبی از برچسب های زبانی برای طبقه بندی داده های بزرگ
منبع:
IEEE - Fuzzy Systems (FUZZ-IEEE), 2016 IEEE International Conference
نویسنده:
Alberto Fernandez, Sara del Rıo , Francisco Herrera
چکیده انگلیسی:
The treatment and processing of Big Data problems
imply an essential advantage for researchers and corporations.
This is due to the huge quantity of knowledge that is hidden
within the vast amount of information that is available nowadays.
In order to be able to address with such volume of information
in an efficient way, the scalability for Big Data applications is
achieved by means of the MapReduce programming model. It is
designed to divide the data into several chunks or groups that are
processed in parallel, and whose result is “assembled” to provide
a single solution.
Focusing on classification tasks, Fuzzy Rule Based Classification Systems have shown interesting results with a MapReduce
approach for Big Data. It is well known that the behaviour of
these type of systems can be further improved in synergy with
Evolutionary Algorithms, leading to Evolutionary Fuzzy Systems.
However, to be best of our knowledge there are no developments
in this field yet.
In this work, we propose a first Evolutionary Fuzzy System
for Big Data problems. It consists of an initial Knowledge
Based build by means of the Chi-FRBCS-BigData algorithm,
followed by a genetic tuning of the Data Base by means of
the 2-tuples representation. This way, the fuzzy labels will be
better contextualized within every subset of the problem, and the
coverage of the Rule Base will be enhanced. Then, the Knowledge
Bases from each Map process are joined to build a ensemble
classifier. Experimental results show the improvement achieved
by this model with respect to the standard Chi-FRBCS-BigData
approach, and opens the way for promising future work on the
topic.
Keywords: Big data | Data models | Programming | Training | Fuzzy systems | Pragmatics | Tuning
قیمت: رایگان
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