Data systematic purifying analysis in data mining

Yu Ting Cheng, Ben Chang Shia, Jun Yuan Kuo, Hui Ru Yang

研究成果: 書貢獻/報告類型會議貢獻

摘要

A goal database and an auxiliary database utilizing functional mapping make the database combine as a great database, then imputes the missing data or the rare data missing in the database. In order to improve the data analysis efficiency, this research proposed the Data SPA (Data Systematic Purifying Analysis) to purify the data systematically. This research has applied three kinds of methods to evaluate the data. After the process of the Data SPA, it can be easily understand that the Data SPA really has good effect on data mining, because it can increase the amount of information of the data and improve the data evaluation efficiency.

原文英語
主出版物標題2009 WRI World Congress on Computer Science and Information Engineering, CSIE 2009
頁面287-290
頁數4
4
DOIs
出版狀態已發佈 - 2009
對外發佈Yes
事件2009 WRI World Congress on Computer Science and Information Engineering, CSIE 2009 - Los Angeles, CA, 美国
持續時間: 三月 31 2009四月 2 2009

其他

其他2009 WRI World Congress on Computer Science and Information Engineering, CSIE 2009
國家美国
城市Los Angeles, CA
期間3/31/094/2/09

ASJC Scopus subject areas

  • Computer Science Applications
  • Hardware and Architecture
  • Information Systems
  • Software

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  • 引用此

    Cheng, Y. T., Shia, B. C., Kuo, J. Y., & Yang, H. R. (2009). Data systematic purifying analysis in data mining. 於 2009 WRI World Congress on Computer Science and Information Engineering, CSIE 2009 (卷 4, 頁 287-290). [5171004] https://doi.org/10.1109/CSIE.2009.908