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Two phase combined model to improve the accuracy of indoor location fingerprinting

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Wi-Fi Fingerprinting based Indoor Positioning System (IPS) aims to help locate and navigate users inside buildings. It has become a popular research topic in recent years with two goals of removing redundant data and increasing positioning accuracy and it has produced acceptable results. In this paper, we propose a feature reduction method and apply a machine learning model that combines two-phases.
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Two phase combined model to improve the accuracy of indoor location fingerprinting

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