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CIKM
2001
Springer

SQL Database Primitives for Decision Tree Classifiers

13 years 7 months ago
SQL Database Primitives for Decision Tree Classifiers
Scalable data mining in large databases is one of today's challenges to database technologies. Thus, substantial effort is dedicated to a tight coupling of database and data mining systems leading to database primitives supporting data mining tasks. In order to support a wide range of tasks and to be of general usage these primitives should be rather building blocks than implementations of specific algorithms. In this paper, we describe primitives for building and applying decision tree classifiers. Based on the analysis of available algorithms and previous work in this area we have identified operations which are useful for a number of classification algorithms. We discuss the implementation of these primitives on top of a commercial DBMS and present experimental results demonstrating the performance benefit.
Kai-Uwe Sattler, Oliver Dunemann
Added 23 Aug 2010
Updated 23 Aug 2010
Type Conference
Year 2001
Where CIKM
Authors Kai-Uwe Sattler, Oliver Dunemann
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