XGBOD: Improving Supervised Outlier Detection with Unsupervised Representation Learning

1 Dec 2019Yue ZhaoMaciej K. Hryniewicki

A new semi-supervised ensemble algorithm called XGBOD (Extreme Gradient Boosting Outlier Detection) is proposed, described and demonstrated for the enhanced detection of outliers from normal observations in various practical datasets. The proposed framework combines the strengths of both supervised and unsupervised machine learning methods by creating a hybrid approach that exploits each of their individual performance capabilities in outlier detection... (read more)

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