Optimal outlier removal in high-dimensional spaces

Optimal Outlier Removal in High-Dimensional Spa es

RNN (Reverse Nearest Neighbour) in Unproven Reserve Based Outlier Discovery

Outlier detection refers to task of identifying patterns. They don’t conform establish regular behavior. Outlier detection in highdimensional data presents various challenges resulting from the “curse of dimensionality”. The current view is that distance concentration that is tendency of distances in high-dimensional data to become in discernible making distance-based methods label all points a...

Feature Extraction for Outlier Detection in High-Dimensional Spaces

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 multidimensional data on which traditional detection techniques usually fail to work as expected due to the curse of dimensionality. This paper introduces an efficient feature extraction method which brings nontrivial im...

Robust high-dimensional semiparametric regression using optimized differencing method applied to the vitamin B2 production data

Background and purpose: By evolving science, knowledge, and technology, we deal with high-dimensional data in which the number of predictors may considerably exceed the sample size. The main problems with high-dimensional data are the estimation of the coefficients and interpretation. For high-dimension problems, classical methods are not reliable because of a large number of predictor variable...

A Robust Method for Detecting DB-Outliers from High Dimensional Datasets

Outlier detection is a popular technique that can be utilized in many modern applications like financial analysis and fraud detection. As data description becomes complex, operated datasets’ dimensionalities keep monotone increasing. However, current researches find that it is extremely difficult to pick out outliers directly from high dimensional datasets owing to the curse of dimensionality. ...