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...
The outlier detection problem has important applications in the eld of fraud detection, network robustness analysis, and intrusion detection. Most such applications are high dimen...
We propose an efficient sampling based outlier detection method for large high-dimensional data. Our method consists of two phases. In the first phase, we combine a "sampling...
Timothy de Vries, Sanjay Chawla, Pei Sun, Gia Vinh...
Among various feature extraction algorithms, those based on genetic algorithms are promising owing to their potential parallelizability and possible applications in large scale an...
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...