Support Vector Machine for Spatial Variation

Findings: Given it’s ability here to find geographic variances in students admitted to a university, the Support Vector Machine is a good tool for recognizing hidden patterns in a dataset.

Method: the paper tests Support Vector Machine against the more traditional method of Linear Discriminant Analysis.

Good for: Researchers looking for new or additional pattern recognition tools.

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Andris C, Wittenbach J and Cowen D (2013) Support Vector Machine for Spatial Variation. Transactions in GIS. 17(1): 41-61.

This entry was posted in 2013.