A Feature Weighting Based Artificial Bee Colony Algorithm for Data Clustering
محل انتشار: هشتمین کنفرانس بین المللی فناوری اطلاعات ودانش
سال انتشار: 1395
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 784
فایل این مقاله در 5 صفحه با فرمت PDF قابل دریافت می باشد
- صدور گواهی نمایه سازی
- من نویسنده این مقاله هستم
استخراج به نرم افزارهای پژوهشی:
شناسه ملی سند علمی:
ICIKT08_022
تاریخ نمایه سازی: 5 بهمن 1395
چکیده مقاله:
Data clustering is a powerful technique for data analysis that used in many applications. The goal of clustering is to detect groups that objects of each group have the most similarity together. Artificial bee colony (ABC) is a simple algorithm with few control parameters to solve clustering problem. However, traditional ABC algorithm is considered the equal importance for all features, while real world applications carry different importance on features. To overcome this issue, we proposed a feature weighting based artificial bee colony (FWABC) algorithm for data clustering. The proposed algorithm considers a specific importance to each feature. The performance of the proposed method has been tested on various datasets and compared to well-known and state-of-the-art methods, the reported results show that the proposed method outperforms other methods.
کلیدواژه ها:
نویسندگان
Manijeh Reisi
Department of Computer Engineering University of Kurdistan Sanandaj, Iran
Parham Moradi
Department of Computer Engineering University of Kurdistan Sanandaj, Iran
Alireza Abdollahpouri
Department of Computer Engineering University of Kurdistan Sanandaj, Iran