HAPT: Human Activity Recognition Dataset
In HDcpDetect: Detect Change Points in Means of High Dimensional Data
Description
Usage
Format
Source
Description
This sample data is drawn from the Human Activity Recognition (HAPT) Dataset on the UCI Machine Learning Repository. The original dataset includes sensor recordings from 30 subjects performing a range of daily activities. The data has 561 attributes, consisting of different accelerometer and gyroscope measurements. A small portion of the overall dataset (10 seconds of recordings for subject A) is included in this package.
Usage
1
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Source
https://archive.ics.uci.edu/ml/datasets/Human+Activity+Recognition+Using+Smartphones
1. Davide Anguita, Alessandro Ghio, Luca Oneto, Xavier Parra and Jorge L. Reyes-Ortiz. A Public Domain Dataset for Human Activity Recognition Using Smartphones. 21th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2013. Bruges Belgium 24-26 April 2013.
HDcpDetect documentation built on May 2, 2019, 7:24 a.m.
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Description Usage Format Source
Description
This sample data is drawn from the Human Activity Recognition (HAPT) Dataset on the UCI Machine Learning Repository. The original dataset includes sensor recordings from 30 subjects performing a range of daily activities. The data has 561 attributes, consisting of different accelerometer and gyroscope measurements. A small portion of the overall dataset (10 seconds of recordings for subject A) is included in this package.
Usage
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Source
https://archive.ics.uci.edu/ml/datasets/Human+Activity+Recognition+Using+Smartphones
1. Davide Anguita, Alessandro Ghio, Luca Oneto, Xavier Parra and Jorge L. Reyes-Ortiz. A Public Domain Dataset for Human Activity Recognition Using Smartphones. 21th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2013. Bruges Belgium 24-26 April 2013.
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