Sensitive Error Correcting Output Codes

2005 ◽  
pp. 158-172 ◽  
Author(s):  
John Langford ◽  
Alina Beygelzimer
Keyword(s):  
Error Correcting Output Codes

Cost-sensitive design of error correcting output codes

2017 ◽  
Vol 232 (10) ◽  
pp. 1871-1881
Author(s):  
Aijun Xue ◽  
Xiaodan Wang
Keyword(s):  
Classification Problem ◽  
Learning Problems ◽  
Classification Problems ◽  
Cost Sensitive Learning ◽  
Misclassification Costs ◽  
Real World Applications ◽  
Cost Sensitive Classification ◽  
Comparable Performance ◽  
The Given ◽  
Error Correcting Output Codes

Many real world applications involve multiclass cost-sensitive learning problems. However, some well-worked binary cost-sensitive learning algorithms cannot be extended into multiclass cost-sensitive learning directly. It is meaningful to decompose the complex multiclass cost-sensitive classification problem into a series of binary cost-sensitive classification problems. So, in this paper we propose an alternative and efficient decomposition framework, using the original error correcting output codes. The main problem in our framework is how to evaluate the binary costs for each binary cost-sensitive base classifier. To solve this problem, we proposed to compute the expected misclassification costs starting from the given multiclass cost matrix. Furthermore, the general formulations to compute the binary costs are given. Experimental results on several synthetic and UCI datasets show that our method can obtain comparable performance in comparison with the state-of-the-art methods.

Sub-class Error-Correcting Output Codes

2008 ◽  
pp. 494-504 ◽  
Author(s):  
Sergio Escalera ◽  
Oriol Pujol ◽  
Petia Radeva
Keyword(s):  
Error Correcting Output Codes

Error-Correcting Output Codes in the Framework of Deep Ordinal Classification

2021 ◽  
pp. 3-13
Author(s):  
Javier Barbero-Gómez ◽  
Pedro Antonio Gutiérrez ◽  
César Hervás-Martínez
Keyword(s):  
Ordinal Classification ◽  
Error Correcting Output Codes
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