In this project, I researched the best model to predict user activities based on motion sensor data. I tried several models and features to understand which would give the best results. To choose the best Machine Learning model, I used K-fold Cross-Validation in Spark MLlib.
I evaluated the model using accuracy. My model achieved 90% accuracy when trained on 70% of the data and tested on the remaining 30%. Overall, this project aimed to demonstrate the use of Spark MLlib for Machine Learning tasks and the importance of selecting the best model for a given problem.
