Mining boundary effects in areally referenced spatial data using the Bayesian information criterion.
Pei LiSudipto BanerjeeAlexander M. McBeanPublished in: GeoInformatica (2011)
Keyphrases
- spatial data
- bayesian information criterion
- frequent neighboring class set
- spatial databases
- geographic information systems
- model selection
- spatial data mining
- spatial objects
- spatial clustering
- spatial datasets
- r tree
- geospatial data
- spatial queries
- geographical information systems
- geo spatial
- information criterion
- gaussian mixture model
- mixture model
- data mining
- data analysis
- spatial analysis
- geographical information
- spatial data management
- geographic information
- spatial relationships
- frequent patterns
- unsupervised learning
- selection criterion
- cross validation
- knowledge discovery
- probabilistic model
- high dimensional
- object recognition
- akaike information criterion
- machine learning