In many classification problems objects should be rejected when the confidence in their
classification is too low. An example is a face recognition problem where the faces of a …

The Mahalanobis distance between pairs of multivariate observations is used as a measure
of similarity between the observations. The theoretical distribution is derived, and the result …

The ever-increasing volume of spatial data has greatly challenged our ability to extract
useful but implicit knowledge from them. As an important branch of spatial data mining …

In this study, outliers are classified into three types:(1) range outliers;(2) spatial outliers; and
(3) relationship outliers, defined as observations that fall outside of the values expected from …

Diagnostic tools must rely on robust high-breakdown methodologies to avoid distortion in
the presence of contamination by outliers. However, a disadvantage of having a single, even …

In recent years, there has been a growing interest in statistical methods for the analysis of
spatially referenced data. The spatial dependence structure modeling is an indispensable …

Population density data are available to the European Commission (EC) at the level of the
commune (NUTS5). The size of communes is very heterogeneous across the EU. Hence this …

The detection of spatially contiguous clusters is a relevant task in geostatistics since near
located observations might have similar features than distant ones. Spatially compact …

The impact of high-grade data on resource estimation has been a longstanding topic of
interest in the mining industry. Concerns related to possible over-estimation of resources in …

Local based approach is a major category of methods for spatial outlier detection (SOD).
Currently, there is a lack of systematic analysis on the statistical properties of this framework …