Week 3 project assignment for Coursera Getting and Cleaning Data course
The "run_analysis.R" in this repo generates a "tidy.txt" on the current directory after reading input files representing data collected from accelerometers from Samsung Galaxy S smartphone.
A zip file with all input files and their description is available at: http://archive.ics.uci.edu/ml/datasets/Human+Activity+Recognition+Using+Smartphones
In order to download the input files, click on "Download Data Folder" and then at "UCI HAR Dataset.zip", or go directly to the zip file URL below:
http://archive.ics.uci.edu/ml/machine-learning-databases/00240/UCI%20HAR%20Dataset.zip
The input files for the project can be also temporarily found also at: https://d396qusza40orc.cloudfront.net/getdata%2Fprojectfiles%2FUCI%20HAR%20Dataset.zip
The "CodeBook.md" in this repo details the variables, data, and any transformations or work performed by "run_analysis.R" and the "tidy.txt" it generates.
This script is distributed AS-IS and no responsibility implied or explicit can be addressed to the author or their institutions for its use or misuse. Any commercial use is prohibited.
Use of the input dataset in publications must be acknowledged by referencing the following publication:
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