کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
488652 703922 2015 9 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Integrating Data Selection and Extreme Learning Machine for Imbalanced Data
ترجمه فارسی عنوان
یکپارچه سازی انتخاب داده ها و دستگاه یادگیری افراطی برای داده های عدم تعادل؟
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر علوم کامپیوتر (عمومی)
چکیده انگلیسی

Extreme Learning Machine (ELM) is one of the artificial neural network method that introduced by Huang, this method has very fast learning capability. ELM is designed for balance data. Common problems in real-life is imbalanced data problem. So, for imbalanced data problem needs special treatment, because characteristics of the imbalanced data can decrease the accuracy of the data classification. The proposed method in this study is modified ELM to overcome the problems of imbalanced data by integrating the data selection process, which is called by Integrating the data selection and extreme learning machine (IDELM. Performances of learning method are evaluated using 13 imbalanced data from UCI Machine Learning Repository and Benchmark Data Sets for Highly Imbalanced Binary Classification (BDS). The validation includes comparison with some learning algorithms and the result showcases that average perform of our proposed learning method is compete and even outperform of some algorithm in some cases.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Procedia Computer Science - Volume 59, 2015, Pages 221-229