文章基本信息

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 等
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.