Human activity recognition using smartphone data.
This repository includes code from a data mining project. The data set can be accessed from the UCI Machine Learning Repository. The goal of the project is to predict 6 classes of activity (walking, walking upstairs, walking downstairs, sitting, standing, and laying) based on data gathered from a cell phone accelerometer and gyroscope.
SVM probably gives the best results. More coming.
- Trees
- basics
- picture of 2-category case
- SVM
- basic
- tune SVM
- naiveBayes
- Neural networks - Parker
- K nearest neighbor
- Silly walks
- basic comparing 2 walkers with trees
- cross validation of at least one model
- apply svm
- multiple walkers
- Understand more about accelerometers and gyroscopes