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  • 标题:K-means based method for handling unlabeled data
  • 本地全文:下载
  • 作者:Sharon Diznarda Álvarez Gómez ; Silvio Amable Machuca Vivar ; Paulina Elizabeth Salas Medina
  • 期刊名称:Universidad y Sociedad
  • 电子版ISSN:2218-3620
  • 出版年度:2021
  • 卷号:13
  • 页码:452-458
  • 语种:Danish
  • 出版社:Universidad de Cienfuegos
  • 摘要:From the development achieved by the current information society, incalculable volumes of data are generated. The exponential growth of information significantly supports people's decision mak-ing in their daily activities. In Ecuador there are many institutions that store the data of their pro-cesses, the tourism sector representing an example of this. However, the data generated exceeds the power of analysis and processing of human beings, sometimes relevant information is present-ed that is not visible to people. The present investigation proposes a solution to the described prob-lem starting from the development of a method for the treatment of unlabeled data.The proposed method is based on the unsupervised k-means algorithm. The proposal has been implemented from the stored data set of the tourism sector in the City of Riobamba.
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