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ClusterNN: a hybrid classification approach to mobile activity recognition. (2015)
Conference Proceeding
BASHIR, S., DOOLAN, D. and PETROVSKI, A. 2015. ClusterNN: a hybrid classification approach to mobile activity recognition. In Chen, L.L., Steinbauer, M., Khalil, I. and Anderst-Kotsis, G. (eds.) Proceedings of the 13th International advances in mobile computing and multimedia conference (MoMM 2015), 11-13 December 2015, Brussels, Belguim. New York: ACM [online], pages 263-267. Available from: https://doi.org/10.1145/2837126.2837140

Mobile activity recognition from sensor data is based on supervised learning algorithms. Many algorithms have been proposed for this task. One of such algorithms is the K-nearest neighbour (KNN) algorithm. However, since KNN is an instance based algo... Read More about ClusterNN: a hybrid classification approach to mobile activity recognition..