کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4978398 | 1452369 | 2017 | 5 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
featsel: A framework for benchmarking of feature selection algorithms and cost functions
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
نرم افزار
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
In this paper, we introduce featsel, a framework for benchmarking of feature selection algorithms and cost functions. This framework allows the user to deal with the search space as a Boolean lattice and has its core coded in C++ for computational efficiency purposes. Moreover, featsel includes Perl scripts to add new algorithms and/or cost functions, generate random instances, plot graphs and organize results into tables. Besides, this framework already comes with dozens of algorithms and cost functions for benchmarking experiments. We also provide illustrative examples, in which featsel outperforms the popular Weka workbench in feature selection procedures on data sets from the UCI Machine Learning Repository.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: SoftwareX - Volume 6, 2017, Pages 193-197
Journal: SoftwareX - Volume 6, 2017, Pages 193-197
نویسندگان
Marcelo S. Reis, Gustavo Estrela, Carlos Eduardo Ferreira, Junior Barrera,