Please use this identifier to cite or link to this item: https://dspace.ctu.edu.vn/jspui/handle/123456789/4275
Title: A new approach for determining the prior probabilities in the classification problem by Bayesian method
Authors: Nguyen, Trang Thao
Võ, Văn Tài
Keywords: Classification
Bayes error
BayesC
Prior probability
Issue Date: 2016
Series/Report no.: Adv Data Anal Classif;11 .- p.629–643
Abstract: In this article, we suggest a new algorithm to identify the prior probabilities for classification problem by Bayesian method. The prior probabilities are determined by combining the information of populations in training set and the new observations through fuzzy clustering method (FCM) instead of using uniform distribution or the ratio of sample or Laplace method as the existing ones. We next combine the determined prior probabilities and the estimated likelihood functions to classify the new object. In practice, calculations are performed by Matlab procedures. The proposed algorithm is tested by the three numerical examples including bench mark and real data sets. The results show that the new approach is reasonable and gives more efficient than existing ones.
URI: http://dspace.ctu.edu.vn/jspui/handle/123456789/4275
Appears in Collections:Tạp chí quốc tế

Files in This Item:
File Description SizeFormat 
_file_2.57 MBAdobe PDFView/Open
Your IP: 3.238.147.211


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.