: A concept for identification of candidates for outliers is presented, with a focus on nominal variables. The database concerned is searched for rules that are almost universally...
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...
Outliers are very common in the environmental data monitored by a sensor network consisting of many inexpensive, low fidelity, and frequently failed sensors. The limited battery ...
Current outlier detection schemes typically output a numeric score representing the degree to which a given observation is an outlier. We argue that converting the scores into wel...
Outlier analysis is an important task in data mining and has attracted much attention in both research and applications. Previous work on outlier detection involves different type...
Wen Jin, Yuelong Jiang, Weining Qian, Anthony K. H...
Sensor networks play an important role in applications concerned with environmental monitoring, disaster management, and policy making. Effective and flexible techniques are need...
We propose a new statistical approach to the problem of inlier-based outlier detection, i.e., finding outliers in the test set based on the training set consisting only of inlier...
Shohei Hido, Yuta Tsuboi, Hisashi Kashima, Masashi...
It is well understood that Mobile Ad Hoc Networks (MANETs) are extremely susceptible to a variety of attacks, and traditional security mechanisms do not work well. Many security sc...
Many outlier detection methods do not merely provide the decision for a single data object being or not being an outlier but give also an outlier score or “outlier factor” sig...