shidaiwei626 / Human-Activity-Recognition-with-Smartphones

Jupyter notebook using Human Activity Recognition with Smartphones database via Support Vector Machine

Geek Repo:Geek Repo

Github PK Tool:Github PK Tool

Human-Activity-Recognition-with-Smartphones

The objective

Given a database built from the recordings of 30 study participants performing activities of daily living (ADL) while carrying a waist-mounted smartphone with embedded inertial sensors. Classify activities into one of the six activities performed.

Solution

In the Jupyter notebook you can see an implementation of Support Vector Machine algorithm using sklean library for python. This supervised learning model implicitly maps their inputs into high-dimensional feature spaces and separate in categories. Accuracy of the model achieve 96% after using a recurrent feature extraction with cross validation method.

About

Jupyter notebook using Human Activity Recognition with Smartphones database via Support Vector Machine


Languages

Language:Jupyter Notebook 100.0%