Comparative Analysis of XGBoost and Minirocket Algortihms for Human Activity Recognition

arXiv:2402.18296v1 Announce Type: new
Abstract: Human Activity Recognition (HAR) has been extensively studied, with recent emphasis on the implementation of advanced Machine Learning (ML) and Deep Learning (DL) algorithms for accurate classification. This study investigates the efficacy of two ML algorithms, eXtreme Gradient Boosting (XGBoost) and MiniRocket, in the realm of HAR using data collected from smartphone sensors. The experiments are conducted on a dataset obtained from the UCI repository, comprising accelerometer and gyroscope signals captured from 30 volunteers performing …

abstract advanced algorithms analysis arxiv boosting classification comparative analysis cs.lg deep learning gradient human implementation machine machine learning ml algorithms recognition study type xgboost