PCA based hybrid hyperplane margin clustering and regression for indoor WLAN localization

Abstract

Based on the Principal Component Analysis (PCA), a novel hybrid Support Vector Machine (SVM) Clustering and Regression (SVMCR) approach used for indoor Wireless Local Area Network (WLAN) localization is proposed in this paper. First of all, we rely on the SVM Clustering (SVMC) to conduct the classification for the sake of narrowing down the search space of… (More)
DOI: 10.1109/CHINACOM.2015.7497969

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Cite this paper

@article{Li2015PCABH, title={PCA based hybrid hyperplane margin clustering and regression for indoor WLAN localization}, author={Lingxia Li and Ming Xiang and Mu Zhou and Zengshan Tian and Yunxia Tang}, journal={2015 10th International Conference on Communications and Networking in China (ChinaCom)}, year={2015}, pages={377-381} }