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  • 标题:Survey on Types of Bug Reports and General Classification Techniques in Data Mining
  • 本地全文:下载
  • 作者:Smita Mishra ; Somesh Kumar
  • 期刊名称:International Journal of Computer Science and Information Technologies
  • 电子版ISSN:0975-9646
  • 出版年度:2015
  • 卷号:6
  • 期号:2
  • 页码:1578-1583
  • 出版社:TechScience Publications
  • 摘要:Data mining is the process of extraction of hidden and useful information from huge data. It is also called knowledge discovery process from data. Bug tracking systems are made to manage bug reports, which are collected from various sources. These bug reports are needed to be labeled as security bug reports or non security bug reports. Data mining uses to apply mining algorithm to extract information which is stored in bug tracking systems. Classification is a task of data mining. A data mining system can be classified according to the kinds of databases mined. Database systems can be classified according to different criteria (such as data models, or the types of data or applications involved), each of which may require its own data mining technique. Data mining systems can therefore be classified accordingly. This paper present a survey on several classification techniques which are generally used for data mining such as naïve bayes, decision tree, K- nearest neighbor, Rule based, neural network etc.
  • 关键词:Bug report; classification; naïve bayes; decision;tree; K-nearest neighbor; Rule based; neural network
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