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صفحه اصلی
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سی امین کنفرانس بین المللی مهندسی برق
RDOD: A Robust Distance-based Technique for Outlier Detection
نویسندگان :
Reza Heydari gharaei
1
Hossein Nezamabadi-pour
2
1- دانشگاه شهید باهنر کرمان
2- دانشگاه شهید باهنر کرمان
کلمات کلیدی :
outlier detection،distance-based method،k nearest neighbor،outlier،anomaly detection
چکیده :
Outlier detection is an important topic in data mining and has been employed in various sciences. Numerous outlier detection methods have been proposed so far; one of the most prominent categories of these methods is based on k-nearest neighbor (kNN). In the present study, an efficient and robust distance-based outlier detection method is presented. One of the main challenges of methods based on k-nearest neighbor is their high dependency on parameter k. The proposed method, however, reduces the sensitivity to k while maintaining the high preciseness of the algorithm. The proposed method was evaluated in two-dimensional synthetic and multidimensional real datasets and compared with some state-of-theart algorithms in the field. The results of the experiments proved the effectiveness of the proposed method.
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بیشتر
ثمین همایش، سامانه مدیریت کنفرانس ها و جشنواره ها - نگارش 43.6.0
