CSVdivya21/Human-Activity-Recognition-using-Random-Forest

Human Activity Recognition using Wearable devices like Accelerometer is an useful application of ML in ioT which is explored in this repo

Human-Activity-Recognition-using-Random-Forest

Build a Random Forest model to classify human activities into 6 main classes namely - Laying, sitting, standing, walk, walk-up and walk-down. The designed random forest classifier acheives an accuracy of 94% on the test data.