The project aims to analyze the data of human activity recognition using smartphone. Original data is from: https://d396qusza40orc.cloudfront.net/getdata%2Fprojectfiles%2FUCI%20HAR%20Dataset.zip
A full description of the data is available: http://archive.ics.uci.edu/ml/datasets/Human+Activity+Recognition+Using+Smartphones
- Merge the test and train datasets into one dataset.
- Rename the variables, i.e., column names in the dataset.
- Extracts only the measurements on the mean and standard deviation in the dataset.
- Replace the values by names in "activity" column.
- Calculate the average of each variable for each activity and each subject in the dataset.
(1) A R script named run_analysis.R to perform the analysis. (2) A README.md file includes the details of the project. (3) A code book describing the variables, i.e., column names.
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By default, the orginal data should be downloaded to "./data/" in working directory, otherwise the path at the beginning of the script should be changed.
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Once the data path is specified, NO extra parameters are required to run the code. With successful execution, an output file named step_5_tidy_data.txt should be generated in your working directory.
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You may have memory allocation issue due to the large input datatsets(train/X_train.txt and test/X_test.txt).
Contact me if you have quetions about this project: jjj1304@gmail.com
Use of this dataset in publications must be acknowledged by referencing the following publication [1]
[1] Davide Anguita, Alessandro Ghio, Luca Oneto, Xavier Parra and Jorge L. Reyes-Ortiz. Human Activity Recognition on Smartphones using a Multiclass Hardware-Friendly Support Vector Machine. International Workshop of Ambient Assisted Living (IWAAL 2012). Vitoria-Gasteiz, Spain. Dec 2012
This dataset is distributed AS-IS and no responsibility implied or explicit can be addressed to the authors or their institutions for its use or misuse. Any commercial use is prohibited.
Jorge L. Reyes-Ortiz, Alessandro Ghio, Luca Oneto, Davide Anguita. November 2012.