DocumentCode :
3282030
Title :
Tree Decomposition of Multiclass Problems
Author :
Lorena, Ana C. ; de Carvalho, A.C.P.
Author_Institution :
Univ. Fed. do ABC, Santo Andre
fYear :
2008
fDate :
26-30 Oct. 2008
Firstpage :
189
Lastpage :
194
Abstract :
Several popular machine learning techniques are originally designed for the solution of two-class problems. However, several classification problems have more than two classes. One approach to deal with multiclass problems using binary classifiers is to decompose the multiclass problem into multiple binary subproblems disposed in a binary tree. This approach requires a binary partition of the classes for each node of the tree, which defines the tree structure. This paper presents two algorithms to determine the tree structure taking into account information collected from the used dataset. This approach allows the tree structure to be determined automatically for any multiclass dataset.
Keywords :
learning (artificial intelligence); pattern classification; tree data structures; binary classifier problem; binary tree structure decomposition; machine learning technique; multiclass dataset; Binary trees; Classification tree analysis; Clustering algorithms; Machine learning; Neural networks; Partitioning algorithms; Support vector machine classification; Support vector machines; Tree data structures; Voting; Machine Learning; decomposition strategies; multiclass classification;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 2008. SBRN '08. 10th Brazilian Symposium on
Conference_Location :
Salvador
ISSN :
1522-4899
Print_ISBN :
978-1-4244-3219-6
Electronic_ISBN :
1522-4899
Type :
conf
DOI :
10.1109/SBRN.2008.43
Filename :
4665914
Link To Document :
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