Performance Evaluation of Classifiers on WISDM Dataset for Human Activity Recognition-Reference-Cited by-同舟云学术

Performance Evaluation of Classifiers on WISDM Dataset for Human Activity Recognition

Published:2016 Issue: Volume: Page:
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Container-title:Proceedings of the Second International Conference on Information and Communication Technology for Competitive Strategies - ICTCS '16
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Author:

Walse K. H.¹,Dharaskar R. V.²,Thakare V. M.³

Affiliation:

1. Dept. of Computer Science and Engg., Anuradha Engineering College, Chikhli, India

2. Disha Technical Campus, Raipur, CG, India

3. P.G. Dept. of Computer Sci. & Engg., S.G.B. Amravati University, Amravati India

Publisher

ACM Press

Reference10 articles.

1. G. M. Weiss and J. W. Lockhart, "A comparison of alternative client/server architectures for ubiquitous mobile sensor-based applications," in Proceedings of the 2012 ACM Conference on Ubiquitous Computing - UbiComp '12, 2012, p. 721.

2. J. R. Kwapisz, G. M. Weiss, and S. a. Moore, "Activity recognition using cell phone accelerometers," ACM SIGKDD Explor. Newsl., vol. 12, no. 2, p. 74, 2011.

3. J. W. Lockhart, "Mobile Sensor Data Mining," Fordham Undergrad. Res. Journal2, vol. 1, pp. 67--68, 2011.

4. J. W. Lockhart, "The Benefits of Personalized Data Mining Approaches to Human Activity Recognition with Smartphone Sensor Data," Fordham University, New york, 2014.

5. J. W. Lockhart and G. M. Weiss, "The Benefits of Personalized Smartphone-Based Activity Recognition Models," in 2014 SIAM International Conference on Data Mining, 2014, p. 9.

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