US Counties dataset for Spatial Outlier Detection
- Rottoli, G
DOI Publisher
Data Archiving and Networked Services (DANS)Abstract
This dataset was used in the validation of the information mining process for discovery of spatial outlier
This dataset was used in the validation of the information mining process for discovery of spatial outlier
Outlier detection is often a key task in a statistical analysis and helps guard against poor decisio...
In this paper, we propose an iterative self-organizing map approach for spatial outlier detection (I...
The detection of spatial clusters and outliers is critical to a number of spatial data analysis tech...
A spatial outlier is a spatially referenced object whose non spatial attribute value is significantl...
Outlier detection focuses on identifying abnormal patterns from large data sets. In this thesis, we ...
Abstract: Outlier detection concerns discovering some unusual data whose behavior is exceptional com...
Outlier detection techniques in spatial data should allow to identify two types of outliers: global...
Outlier detection, as a data mining task, is to identify a small set of data that is considerably di...
Identification of outliers can lead to the discovery of unexpected, interesting, and implicit knowle...
In the field of geography,a spatial outlier is an object whose non-spatial attribute value is signif...
Spatial data are characterized by statistical units, with known geographical positions, on which non...
Spatial data are characterized by statistical units, with known geographical positions, on which non...
Multivariate spatial data are geographical locations on which non spatial variables are measured. S...
AbstractDecision support systems are computer based programs which assists decision makers in effect...
In this information age, the problem of data quality deserves more attention than it is getting. Con...
Outlier detection is often a key task in a statistical analysis and helps guard against poor decisio...
In this paper, we propose an iterative self-organizing map approach for spatial outlier detection (I...
The detection of spatial clusters and outliers is critical to a number of spatial data analysis tech...
A spatial outlier is a spatially referenced object whose non spatial attribute value is significantl...
Outlier detection focuses on identifying abnormal patterns from large data sets. In this thesis, we ...
Abstract: Outlier detection concerns discovering some unusual data whose behavior is exceptional com...
Outlier detection techniques in spatial data should allow to identify two types of outliers: global...
Outlier detection, as a data mining task, is to identify a small set of data that is considerably di...
Identification of outliers can lead to the discovery of unexpected, interesting, and implicit knowle...
In the field of geography,a spatial outlier is an object whose non-spatial attribute value is signif...
Spatial data are characterized by statistical units, with known geographical positions, on which non...
Spatial data are characterized by statistical units, with known geographical positions, on which non...
Multivariate spatial data are geographical locations on which non spatial variables are measured. S...
AbstractDecision support systems are computer based programs which assists decision makers in effect...
In this information age, the problem of data quality deserves more attention than it is getting. Con...
Outlier detection is often a key task in a statistical analysis and helps guard against poor decisio...
In this paper, we propose an iterative self-organizing map approach for spatial outlier detection (I...
The detection of spatial clusters and outliers is critical to a number of spatial data analysis tech...
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