این سایت در حال حاضر پشتیبانی نمی شود و امکان دارد داده های نشریات بروز نباشند
Journal of Artificial Intelligence and Data Mining، جلد ۱۱، شماره ۴، صفحات ۵۱۷-۵۲۴
عنوان فارسی
چکیده فارسی مقاله
کلیدواژه‌های فارسی مقاله
عنوان انگلیسی Auto-UFSTool: An Automatic Unsupervised Feature Selection Toolbox for MATLAB
چکیده انگلیسی مقاله Various data analysis research has recently become necessary in to find and select relevant features without class labels using Unsupervised Feature Selection (UFS) approaches. Despite the fact that several open-source toolboxes provide feature selection techniques to reduce redundant features, data dimensionality, and computation costs, these approaches require programming knowledge, which limits their popularity and has not adequately addressed unlabeled real-world data. Automatic UFS Toolbox (Auto-UFSTool) for MATLAB, proposed in this study, is a user-friendly and fully-automatic toolbox that utilizes several UFS approaches from the most recent research. It is a collection of 25 robust UFS approaches, most of which were developed within the last five years. Therefore, a clear and systematic comparison of competing methods is feasible without requiring a single line of code. Even users without any previous programming experience may utilize the actual implementation by the Graphical User Interface (GUI). It also provides the opportunity to evaluate the feature selection results and generate graphs that facilitate the comparison of subsets of varying sizes. It is freely accessible in the MATLAB File Exchange repository and includes scripts and source code for each technique. The link to this toolbox is freely available to the general public on: bit.ly/AutoUFSTool
کلیدواژه‌های انگلیسی مقاله Unsupervised Feature Selection, MATLAB, Automatic Toolbox, Dimension Reduction, Unsupervised learning
نویسندگان مقاله Farhad Abedinzadeh Torghabeh |
Department of Biomedical Engineering, Mashhad Branch, Islamic Azad University, Mashhad, Iran.

Yeganeh Modaresnia |
Department of Biomedical Engineering, Mashhad Branch, Islamic Azad University, Mashhad, Iran

Seyyed Abed Hosseini |
Department of Electrical Engineering, Mashhad Branch, Islamic Azad University, Mashhad, Iran.

نشانی اینترنتی https://jad.shahroodut.ac.ir/article_2945_b800e2353192ae87cb9dac3cf6a54571.pdf
فایل مقاله فایلی برای مقاله ذخیره نشده است
کد مقاله (doi)
زبان مقاله منتشر شده en
موضوعات مقاله منتشر شده
نوع مقاله منتشر شده
برگشت به: صفحه اول پایگاه   |   نسخه مرتبط   |   نشریه مرتبط   |   فهرست نشریات