Density Weighted Core Support Vector Machine

سال انتشار: 1394
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 339

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شناسه ملی سند علمی:

JR_ACSIJ-4-6_021

تاریخ نمایه سازی: 4 خرداد 1395

چکیده مقاله:

Core Vector Machine (CVM) can be used to deal with large datasets classification problem, but CVM do not consider the densitydistribution of the data. In order to obtain the optimal descriptionof the data, we propose a density weighted core support vectormachine (DWCVM). In the proposed DWCVM, the relativedensity of each data point is based on the density distribution ofthe target data using the k-nearest neighbor (k-NN) approach.Experimental results on several benchmark data sets show thatthe performance of DWCVM is much better than CVM.

نویسندگان

Lu Shuxia

Key Lab. of Machine Learning and Computational Intelligence,College of Mathematics and Information Science, Hebei UniversityBaoding, Hebei 071002,China

Chenxu Zhu

College of Science, Northwest Agriculture & Forestry University,Yangling, Shanxi 712100, China

Caihong Jiao

Key Lab. of MachineLearning and ComputationalIntelligence,College of Mathematicsand Information Science, Hebei UniversityBaoding, Hebei 071002,China