Human Activity Recognition on Smartphone: A Classification Analysis

Shianghau Wu, Yanan Song

Abstract


The study hinged on the human activity recognition on smartphones by using the random forests model and Ada Boost model to make the classification. The study compared the classification results of two models and found the AdaBoost model had the better classification results. The study also found the Ada Boost model had the advantage of less calculation time.


Keywords


Activity Recognition; Random Forests Model; AdaBoost Model; Classification; Machine Learning

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DOI: http://doi.org/10.11591/ijeecs.v12.i9.pp7041-7045

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The Indonesian Journal of Electrical Engineering and Computer Science (IJEECS)
p-ISSN: 2502-4752, e-ISSN: 2502-4760
This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).

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