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文章基本信息

  • 标题:Categorization of Factors Affecting Classification Algorithms Selection
  • 本地全文:下载
  • 作者:Mariam Moustafa Reda ; Mohammad Nassef ; Akram Salah
  • 期刊名称:International Journal of Data Mining & Knowledge Management Process
  • 印刷版ISSN:2231-007X
  • 电子版ISSN:2230-9608
  • 出版年度:2019
  • 卷号:9
  • 期号:4
  • 页码:1-19
  • DOI:10.5121/ijdkp.2019.9401
  • 出版社:Academy & Industry Research Collaboration Center (AIRCC)
  • 摘要:A lot of classification algorithms are available in the area of data mining for solving the same kind of problem with a little guidance for recommending the most appropriate algorithm to use which gives best results for the dataset at hand. As a way of optimizing the chances of recommending the most appropriate classification algorithm for a dataset, this paper focuses on the different factors considered by data miners and researchers in different studies when selecting the classification algorithms that will yield desired knowledge for the dataset at hand. The paper divided the factors affecting classification algorithms recommendation into business and technical factors. The technical factors proposed are measurable and can be exploited by recommendation software tools.
  • 关键词:Classification; Algorithm selection; Factors; Meta-learning; Landmarking
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