Shekhar Project Report ( draft version ) “ Spatial Outlier Detection ”

A spatial outlier is a spatially referenced object whose non-spatial attribute values are significantly different from the values of its neighborhood. Identification of spatial outliers can lead to the discovery of unexpected, interesting, and useful spatial patterns for further analysis. WEKA is a collection of machine learning algorithms for solving real-world data mining problems. It is written in Java and runs on almost any platform. Basic data mining functions as well as regression, association rules and clustering algorithms have also been implemented in WEKA, but their algorithms can only operate on traditional non-spatial database. The purpose of this project is to build a new class, which can detect spatial outlier in a spatial data set.