Pre-processing Large Spatial Data Sets with Bayesian Methods

Authors:
Saara Hyvönen;Esa Junttila;Marko Salmenkivi
Affiliations:
Helsinki Institute for Information Technology, Department of Computer Science, University of Helsinki, Finland;Helsinki Institute for Information Technology, Department of Computer Science, University of Helsinki, Finland;Helsinki Institute for Information Technology, Department of Computer Science, University of Helsinki, Finland
Venue:
PKDD 2007 Proceedings of the 11th European conference on Principles and Practice of Knowledge Discovery in Databases
Year:
2007

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Abstract

Binary data appears in many spatial applications such as dialectology and ecology. We demonstrate that a simple Bayesian modeling approach can be used in pre-processing large spatial data sets with missing or uncertain data. Our experiments on real and synthetic data show that conducting the pre-processing phase before applying conventional data mining methods, such as PCA, clustering or NMF, improves the results significantly.