Temporal Outlier Analysis

Outlier Analysis Outlier Analysis

Finding Outlier DMUs in Data Envelopment Analysis

Spatio-Temporal Outlier Detection Technique

Outlier detection is very important functionality of data mining, it has enormous applications. This paper proposes a clustering based approach for outlier detection using spatio-temporal data. It uses three step approach to detect spatiotemporal outliers. In the first step of outlier detection, clustering is performed on the spatio-temporal dataset with proposed Spatio-Temporal Shared Nearest ...

Spatio-temporal Outlier Detection in Precipitation Data

The detection of outliers from spatio-temporal data is an important task due to the increasing amount of spatio-temporal data available, and the need to understand and interpret it. Due to the limitations of previous data mining techniques, new techniques to detect spatio-temporal outliers need to be developed. In this paper, we propose a spatio-temporal outlier detection algorithm called Outst...

Unsupervised Outlier Profile Analysis

In much of the analysis of high-throughput genomic data, "interesting" genes have been selected based on assessment of differential expression between two groups or generalizations thereof. Most of the literature focuses on changes in mean expression or the entire distribution. In this article, we explore the use of C(α) tests, which have been applied in other genomic data settings. Their use f...