Title
Multicategory classification based on the hypercube self-organizing mapping (SOM) scheme
Abstract
A new multicalss recognition strategy is proposed in this paper, where the self-organizing mapping (SOM) scheme with a hypercube mapped space is used to represent each category in a binary string format and a binary classifier is assigned to each bit in the string. Our strategy outperforms the existing approaches in the prior knowledge requirement, the number of binary classifiers, computation complexity, storage requirement, decision boundary complexity and recognition rate.
Year
DOI
Venue
2006
10.1007/11881070_17
ICNC (1)
Keywords
Field
DocType
computational complexity
Binary classification,Computer science,Self-organization,Pseudorandom binary sequence,Multicategory,Artificial intelligence,Decision boundary,String (computer science),Machine learning,Hypercube,Binary number
Conference
Volume
Issue
ISSN
4221 LNCS - I
null
0302-9743
ISBN
Citations 
PageRank 
3-540-45901-4
1
0.35
References 
Authors
3
3
Name
Order
Citations
PageRank
Lan Du127234.83
Junying Zhang2867.59
Zheng Bao31985155.03