Outlier detection has recently become an important problem in many industrial and financial applications. In this paper, a novel feature bagging approach for detecting outliers in...
In this paper we address the problem of selecting variables or features in a regression model in the presence of both additive (vertical) and leverage outliers. Since variable sel...
Abstract. Existing studies in outlier detection mostly focus on detecting outliers in full feature space. But most algorithms tend to break down in highdimensional feature spaces b...
This work addresses the problem of feature extraction for boosting the performance of outlier detectors in high-dimensional spaces. Recent years have observed the prominence of mu...
Default logic is used to describe regular behavior and normal properties. We suggest to exploit the framework of default logic for detecting outliers - individuals who behave in a...