An Efficient Relational Decision Tree Classification Algorithm

Authors:
Jing-Feng Guo;Jing Li;Wei-Feng Bian
Affiliations:
Yanshan University, China;Yanshan University, China;Yanshan University, China
Venue:
ICNC '07 Proceedings of the Third International Conference on Natural Computation - Volume 03
Year:
2007

Citing 0
Cited 4

Boosting tuple propagation in multi-relational classification

Proceedings of the 15th Symposium on International Database Engineering & Applications
Data mining from multiple heterogeneous relational databases using decision tree classification

Pattern Recognition Letters
Combining heterogeneous classifiers for relational databases

Pattern Recognition
Simple decision forests for multi-relational classification

Decision Support Systems

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Abstract

We present a general approach to speeding up a family of multi-relational data mining algorithms that using ID propagation to obtain the information needed for building decision tree classifier from relational database. Preliminary results of our experiments suggest that the proposed method can yield 1-2 orders of magnitude reductions in the running time of such algorithms without any deterioration in the accuracy of results. The proposed modifications enhance the applicability of decision tree algorithms to significantly relational databases that would otherwise be not feasible in practice.