Minimum Spanning Tree Based Spatial Outlier Mining and Its Applications. Jiaxiang Lin & D.Y. Ye Key Lab of Spatial Data Mining & Information Sharing of Ministry of Education, Fuzhou University, China May, 2008. Motivation.
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Minimum Spanning Tree Based Spatial Outlier Mining and Its Applications
Jiaxiang Lin & D.Y. Ye
Key Lab of Spatial Data Mining & Information Sharing of Ministry of Education,
Fuzhou University, China
May, 2008
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Example:
connected graph
spanning tree (MST)
Cluster 2
Inconsistent edge
Cluster 1
We can “control” the number of clusters by changing the precise definition of an inconsistent edge to be removed !
Loose Integration (VDM)
Plane Sweep Line Algorithm
Inconsistent
Threshold=
Inconsistent edges
MST segmentation, Partitional Clustering
Preliminary work
Outlier score of each candidate s-outliers
Candidate s-outlier display in chart
Iterative test spatial objects, get candidate s-outliers
s-outliers display in ESRI.ArcMap
Real s-outliers