README

What about this repository?

• This project tries to recognize types of body movements based on biometrics signals (linear acceleration, angular velocity, etc.) using supervised learning algorithms (Naive Bayes, SVM and Decision Trees)
• Uses data from a public data repository (UCI Machine Learning Repository): https://archive.ics.uci.edu/ml/datasets/Human+Activity+Recognition+Using+Smartphones
• It's built on Python 2.7.10

How do I get set up?

• It's possible to install dependencies by running pip install -r requirements.txt. If you don't have pip, you can visit this page
• Now, you are can run the main script by tipping python activityRecognition.py on console

Functions

• Data pre-processing / Feature evaluation
• Feature computation
• Boxplots
• Dimensionality reduction
  • Feature selection (Variance threshold)
  • Feature extraction (PCA)
• Classification (Supervised learning)
  • Stratified sampling
  • Naive Bayes, SVC and Decision Tree

Who do I talk to?

• irene.sanchezl93@gmail.com