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