پیاده سازی الگوریتم های نظریه مجموعه راف و نظریه مجموعه راف فازی در بسته R "مجموعه راف"
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|46296||2014||22 صفحه PDF||سفارش دهید||محاسبه نشده|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Information Sciences, Volume 287, 10 December 2014, Pages 68–89
The package RoughSets, written mainly in the R language, provides implementations of methods from the rough set theory (RST) and fuzzy rough set theory (FRST) for data modeling and analysis. It considers not only fundamental concepts (e.g., indiscernibility relations, lower/upper approximations, etc.), but also their applications in many tasks: discretization, feature selection, instance selection, rule induction, and nearest neighbor-based classifiers. The package architecture and examples are presented in order to introduce it to researchers and practitioners. Researchers can build new models by defining custom functions as parameters, and practitioners are able to perform analysis and prediction of their data using available algorithms. Additionally, we provide a review and comparison of well-known software packages. Overall, our package should be considered as an alternative software library for analyzing data based on RST and FRST.