Geo Mining in ELKI

Spatial data mining in ELKI is supported at various places.

Specialized Geo data mining algorithms

Outlier detection:

• CTLuGLSBackwardSearchAlgorithm
• CTLuMeanMultipleAttributes
• CTLuMedianAlgorithm
• CTLuMedianMultipleAttributes
• CTLuMoranScatterplotOutlier
• CTLuRandomWalkEC
• CTLuScatterplotOutlier
• CTLuZTestOutlier
• SLOM
• SOF
• TrimmedMeanApproach

Additionally, you can use existing data mining Algorithms via specialized Distances.

Geo distance functions

Defined for latitude-longitude pairs:

• DimensionSelectingLatLngDistance
• LatLngDistance
• LngLatDistance

See Distances for other distance functions.

Geo data types

• Regular number vectors (e.g., 2-d with longitude and latitude meaning)
• Multi-Polygons

See DataTypes for a complete overview.

Index support

Metrical Index Structures have support for geo data by using geographic distance functions.

Support in R-Trees is not yet complete, as we do not yet have an implementation of a valid min-dist for spatial rectangles on the earth sphere.

Output support

ELKI has specialized output support for geo data:

• elki.result.KMLOutputHandler for producing KML output files