It is known that the error correcting output code (ECOC) technique, when applied to multi-
class learning problems, can improve generalisation performance. One reason for the …

One of the most important topics in information fusion is the combination of individual
classifiers in multi-classifier systems. We have two different tasks in this area: one is the …

Feature location is the process of finding the source code that implements a functional
requirement of a software system. It plays an important role in software maintenance …

Error-correcting output codes (ECOC) are used to design diverse classifier ensembles.
Diversity within ECOC is traditionally measured by Hamming distance. Here we argue that …

Two key factors affecting the performance of Error Correcting Output Codes (ECOC) in
multiclass classification problems are the independence of binary classifiers and the …

Among the proposed methods to deal with multi-class classification problems, the error-
correcting output codes (ECOCs) represents a powerful framework. A key factor in designing …

According to the pros and cons of contourlet transform and multimodality medical imaging,
here we propose a novel image fusion algorithm that combines nonlinear approximation of …

In this paper, we propose an evolutionary approach to the design of output codes for
multiclass pattern recognition problems. This approach has the advantage of taking into …

The error correcting output coding (ECOC) approach to classifier design decomposes a
multi-class problem into a set of complementary two-class problems. We show how to apply …

Abstract Error Correcting Output Coding (ECOC) methods for multiclass classification
present several open problems ranging from the trade-off between their error recovering …