Comparison of Random Forest and Extreme Gradient Boosting Fingerprints to Enhance an indoor Wifi Localization System

Machine Learning framework adds a new dimension to the localization estimation problem. It tries to find the most likely position using processed features in a radio map. This paper compares the performance of two machine learning tools, Random Forest (RF) and Extreme Gradient Boosting (XGBoost), in exploiting the multipath information for Indoor localization problem. The investigation was carried...