Human Activity Recognition — CSE 158

Overview

Final group project for CSE 158 (Web Mining and Recommender Systems, Fall 2025) at UCSD. Built a model to classify human activities — walking, sitting, standing, stairs, and more — from wearable-sensor time-series data. Handled the full pipeline: windowing raw accelerometer/gyroscope streams, engineering time- and frequency-domain features, training classifiers, and comparing performance across model families. Covered feature selection, cross-validation, and error analysis against a confusion matrix.