基于机器学习模型下智能手机APP使用情况聚类分析研究
Journal: Engineering and Management Science DOI: 10.12238/ems.v5i3.6280
Abstract
随着智能手机普及和移动互联网发展，智能手机APP成为人们日常生活中不可或缺一部分。每天，人们使用各种不同APP来满足各种需求，如社交、娱乐、购物、工作等。分析不同群体用户特征以及通过用户APP记录预测未来是否使用APP及使用时长尤其重要。本文通过构建三种聚类模型: kmeans聚类、DBSCAN聚类、层次聚类，并通过轮廓系数、DB指数Calinski-Harabasz指数分析其聚类效果。其中kmeans效果最好，轮廓系数为0.3437，DB指数为0.811884，Calinski-Harabasz指数为58552.461。
Keywords
均值聚类；DBSCAN 聚类；分层聚类
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