Recoding Error-Correcting Output Codes
نویسندگان
چکیده
One of the most widely applied techniques to deal with multiclass categorization problems is the pairwise voting procedure. Recently, this classical approach has been embedded in the Error-Correcting Output Codes framework (ECOC). This framework is based on a coding step, where a set of binary problems are learnt and coded in a matrix, and a decoding step, where a new sample is tested and classified according to a comparison with the positions of the coded matrix. In this paper, we present a novel approach to redefine without retraining, in a problem-dependent way, the one-versus-one coding matrix so that the new coded information increases the generalization capability of the system. Moreover, the final classification can be tuned with the inclusion of a weighting matrix in the decoding step. The approach has been validated over several UCI Machine Learning repository data sets and two real multi-class problems: traffic sign and face categorization. The results show that performance improvements are obtained when comparing the new approach to one of the best ECOC designs (one-versus-one). Furthermore, the novel methodology obtains at least the same performance than the one-versus-one ECOC design.
منابع مشابه
An approach to fault detection and correction in design of systems using of Turbo codes
We present an approach to design of fault tolerant computing systems. In this paper, a technique is employed that enable the combination of several codes, in order to obtain flexibility in the design of error correcting codes. Code combining techniques are very effective, which one of these codes are turbo codes. The Algorithm-based fault tolerance techniques that to detect errors rely on the c...
متن کاملEffectiveness of Error Correcting Output Codes in Multiclass Learning Problems
Classification (machine learning): How does one algorithmically classify the though a more effective approach could be using error correcting codes: @(cs/9501101) Solving Multiclass Learning Problems via Error-Correcting Output Codes. to solving machine learning problems can be broadly useful.
متن کاملLearning efficient error correcting output codes for large hierarchical multi-class problems
We describe a new approach for dealing with hierarchical classification with a large number of classes. We build on Error Correcting Output Codes and propose two algorithms that learn compact, binary, low dimensional class codes from a similarity information between classes. This allows building classification algorithms that performs similarly or better than the standard and performing one-vs-...
متن کاملBias , Variance , and Error Correcting Output Codes forLocal Learners ?
This paper focuses on a bias variance decomposition analysis of a local learning algorithm, the nearest neighbor classiier, that has been extended with error correcting output codes. This extended algorithm often considerably reduces the 0-1 (i.e., classiication) error in comparison with nearest neighbor (Ricci & Aha, 1997). The analysis presented here reveals that this performance improvement ...
متن کاملOne-point Goppa Codes on Some Genus 3 Curves with Applications in Quantum Error-Correcting Codes
We investigate one-point algebraic geometric codes CL(D, G) associated to maximal curves recently characterized by Tafazolian and Torres given by the affine equation yl = f(x), where f(x) is a separable polynomial of degree r relatively prime to l. We mainly focus on the curve y4 = x3 +x and Picard curves given by the equations y3 = x4-x and y3 = x4 -1. As a result, we obtain exact value of min...
متن کامل