Abstract
Processing GIS Data Using Decision Trees and an Inductive Learning Method
Highlights
Spatial data mining (SDM) or knowledge discovery in spatial databases refers to the extraction of implicit knowledge or other patterns that are not explicitly stored in spatial database
The article is organized as follows: in Section I we expose the spatial data mining domain with the spatial classification, in Section II some related work is shown, in Section III we present the C4.5 Decision tree algorithm, Section IV describes the spatial data classification with the model based on Geographic Information System (GIS) data, in Section V which shows the steps of experimental results we analyze and present the results performed and in Section VI we conclude our discussion and we present further directions
We present three tables, in which the results vary on the value of k. These tables expose a part of the results of the implementation of the C4.5 Decision tree algorithm using Weka tool, according to the attributes Cadastral-number and Category-of-use which represent two random values on the model
Summary
Spatial data mining (SDM) or knowledge discovery in spatial databases refers to the extraction of implicit knowledge or other patterns that are not explicitly stored in spatial database. The word spatial refers to the data associated with the geographic location of the earth. A large amount of spatial data have been collected in various applications, ranging from remote sensing to GIS, computer cartography, environmental assessment and planning [1]. The quantity of the collected data is huge, meaning that it is too much human knowledge to analyze it, new and efficient methods are needed to discover knowledge from large spatial databases. Over the last few years, spatial data mining has been often used in many and various applications. Spatial data mining is the analysis of geometric or statistical characteristics and relationships of spatial data [1]
Sign-in/Register to view highlights & summary 
Published Version (
Free)
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call