Binary Classification Trees for Multi-class Classification Problems

Authors:
Jin-Seon Lee;Il-Seok Oh
Affiliations:
-;-
Venue:
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 2
Year:
2003

Citing 3
Cited 4

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Induction of multiclass multifeature split decision trees from distributed data

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Abstract

This paper proposes a binary classification tree aiming atsolving multi-class classification problems using binaryclassifiers. The tree design is achieved in a way that aclass group is partitioned into two distinct subgroups at anode. The node adopts the class-modular scheme toimprove the binary classification capability. Thepartitioning is formulated as an optimization problemand a genetic algorithm is proposed to solve theoptimization problem. The binary classification tree iscompared to the conventional methods in terms ofclassification accuracy and timing efficiency.Experiments were performed with numeral recognitionand touching-numeral pair recognition.