- python 2.7
- numpy
- pandas
- scipy
- sklearn
|-- Code
|-- step_detector.py - Helper functions
|-- train.py - Used to evaluate the best model for detecting the steps and distance
|-- test.py - Reads the TestFiles directory and prints the step_count and distance
|-- TestFiles
|-- Test_i.csv
|-- TrainFiles
|-- Train_i.csv
|-- SessionsSummary.csv
python Code/train.py
Output: classifier.pkl
Grid Search Results:
Best parameters set found for SVR:
{'epsilon': 0.96000000000000008, 'C': 1.4000000000000001, 'kernel': 'linear'}
MSE:
14.57755
Best parameters set found for Lasso:
{'alpha': 0.5}
MSE:
14.4082100964
Best parameters set found for Ridge:
{'alpha': 8.5}
MSE:
14.4199991899
Best parameters set found for LinearRegression:
{'normalize': False}
MSE:
14.2564045671
python Code/test.py