Spectral analysis of 2D outlier layout

Outlier Analysis Outlier Analysis

Outlier Detection with Space Transformation and Spectral Analysis

Detecting a small number of outliers from a set of data observations is always challenging. In this paper, we present an approach that exploits space transformation and uses spectral analysis in the newly transformed space for outlier detection. Unlike most existing techniques in the literature which rely on notions of distances or densities, this approach introduces a novel concept based on lo...

Finding Outlier DMUs in Data Envelopment Analysis

Outlier Removal in 2D Leap Frog Algorithm

In this paper a 2D Leap Frog Algorithm is applied to solve the so-called noisy Photometric Stereo problem. In 3-source Photometric Stereo (noiseless or noisy) an ideal unknown Lambertian surface is illuminated from distant light-source directions (their directions are assumed to be linearly independent). The subsequent goal, given three images is to reconstruct the illuminated object’s shape. U...

Outlier Cluster Formation in Spectral Clustering

Outlier detection and cluster number estimation is an important issue for clustering real data. This paper focuses on spectral clustering, a timetested clustering method, and reveals its important properties related to outliers. The highlights of this paper are the following two mathematical observations: first, spectral clustering’s intrinsic property of an outlier cluster formation, and secon...