Human-Activity-Recognition-from-Accelerometer-Data-Using-Ensemble-Learning

This project aims to classify the human activities using ensemble learning method.

Dataset:

The human activities dataset contains 5 classes (sitting-down, standing-up, standing, walking, and sitting) collected on 8 hours of activities of 4 healthy subjects. The data set is downloaded from

http://groupware.les.inf.puc-rio.br/har#ixzz4Mt0Teae2

Ugulino, W.; Cardador, D.; Vega, K.; Velloso, E.; Milidiu, R.; Fuks, H. Wearable Computing: Accelerometers' Data Classification of Body Postures and Movements. Proceedings of 21st Brazilian Symposium on Artificial Intelligence. Advances in Artificial Intelligence - SBIA 2012. In: Lecture Notes in Computer Science. , pp. 52-61. Curitiba, PR: Springer Berlin / Heidelberg, 2012. ISBN 978-3-642-34458-9. DOI: 10.1007/978-3-642-34459-6_6.