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221
Solving multiclass learning problems via errorcorrecting output codes
 JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH
, 1995
"... Multiclass learning problems involve nding a de nition for an unknown function f(x) whose range is a discrete set containing k>2values (i.e., k \classes"). The de nition is acquired by studying collections of training examples of the form hx i;f(x i)i. Existing approaches to multiclass l ..."
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Cited by 726 (8 self)
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thatlike the other methodsthe errorcorrecting code technique can provide reliable class probability estimates. Taken together, these results demonstrate that errorcorrecting output codes provide a generalpurpose method for improving the performance of inductive learning programs on multiclass
Reducing Multiclass to Binary: A Unifying Approach for Margin Classifiers
 JOURNAL OF MACHINE LEARNING RESEARCH
, 2000
"... We present a unifying framework for studying the solution of multiclass categorization problems by reducing them to multiple binary problems that are then solved using a marginbased binary learning algorithm. The proposed framework unifies some of the most popular approaches in which each class ..."
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Cited by 561 (20 self)
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is compared against all others, or in which all pairs of classes are compared to each other, or in which output codes with errorcorrecting properties are used. We propose a general method for combining the classifiers generated on the binary problems, and we prove a general empirical multiclass loss bound
ErrorCorrecting Output Coding Corrects Bias and Variance
 In Proceedings of the Twelfth International Conference on Machine Learning
, 1995
"... Previous research has shown that a technique called errorcorrecting output coding (ECOC) can dramatically improve the classification accuracy of supervised learning algorithms that learn to classify data points into one of k AE 2 classes. This paper presents an investigation of why the ECOC techniq ..."
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Cited by 170 (5 self)
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ECOC can correct for errors caused by the bias of the learning algorithm. Experiments show that this bias correction ability relies on the nonlocal behavior of C4.5. 1 Introduction Errorcorrecting output coding (ECOC) is a method for applying binary (twoclass) learning algorithms to solve k
Probability Estimation via ErrorCorrecting Output Coding
 In Int. Conf. of Artificial Inteligence and soft computing, Banff,Canada
, 1997
"... Previous research has shown that a technique called errorcorrecting output coding (ECOC) can dramatically improve the classification accuracy of supervised learning algorithms that learn to classify data points into one of k AE 2 classes. In this paper, we will extend the technique so that ECOC can ..."
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Cited by 9 (0 self)
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Previous research has shown that a technique called errorcorrecting output coding (ECOC) can dramatically improve the classification accuracy of supervised learning algorithms that learn to classify data points into one of k AE 2 classes. In this paper, we will extend the technique so that ECOC
Multiclass Learning, Boosting, and ErrorCorrecting Codes
 Proceedings of the Twelfth Annual Conference on Computational Learning Theory
, 1999
"... We focus on methods to solve multiclass learning problems by using only simple and efficient binary learners. We investigate the approach of Dietterich and Bakiri [2] based on errorcorrecting codes (which we call ECC). We distill error correlation as one of the key parameters influencing the perfo ..."
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Cited by 49 (0 self)
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We focus on methods to solve multiclass learning problems by using only simple and efficient binary learners. We investigate the approach of Dietterich and Bakiri [2] based on errorcorrecting codes (which we call ECC). We distill error correlation as one of the key parameters influencing
Using Output Codes to Boost Multiclass Learning Problems
 MACHINE LEARNING: PROCEEDINGS OF THE FOURTEENTH INTERNATIONAL CONFERENCE, 1997 (ICML97)
, 1997
"... This paper describes a new technique for solving multiclass learning problems by combining Freund and Schapire's boosting algorithm with the main ideas of Dietterich and Bakiri's method of errorcorrecting output codes (ECOC). Boosting is a general method of improving the accuracy of a giv ..."
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Cited by 113 (8 self)
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This paper describes a new technique for solving multiclass learning problems by combining Freund and Schapire's boosting algorithm with the main ideas of Dietterich and Bakiri's method of errorcorrecting output codes (ECOC). Boosting is a general method of improving the accuracy of a
Multiclass Learning, Boosting, and ErrorCorrecting Codes
 Proceedings of the Twelfth Annual Conference on Computational Learning Theory
, 1999
"... We focus on methods to solve multiclass learning problems by using only simple and efficient binary learners. We investigate the approach of Dietterich and Bakiri [2] based on errorcorrecting codes (which we call ECC). We distill error correlation as one of the key parameters influencing the ..."
Abstract
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We focus on methods to solve multiclass learning problems by using only simple and efficient binary learners. We investigate the approach of Dietterich and Bakiri [2] based on errorcorrecting codes (which we call ECC). We distill error correlation as one of the key parameters influencing
Multiclass Classification in Image Analysis Via ErrorCorrecting Output Codes
"... A common way to model multiclass classification problems is by means of ErrorCorrecting Output Codes (ECOC). Given a multiclass problem, the ECOC technique designs a codeword for each class, where each position of the code identifies the membership of the class for a given binary problem. A clas ..."
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A common way to model multiclass classification problems is by means of ErrorCorrecting Output Codes (ECOC). Given a multiclass problem, the ECOC technique designs a codeword for each class, where each position of the code identifies the membership of the class for a given binary problem. A
Recoding ErrorCorrecting Output Codes
"... Abstract. 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 ErrorCorrecting Output Codes framework (ECOC). This framework is based on a coding step, where a set of bi ..."
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Cited by 2 (0 self)
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Abstract. 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 ErrorCorrecting Output Codes framework (ECOC). This framework is based on a coding step, where a set
ErrorCorrecting Output Codes: A General Method for Improving Multiclass Inductive Learning Programs
 IN PROCEEDINGS OF AAAI91
, 1991
"... Multiclass learning problems involve finding a definition for an unknown function f(x) whose range is a discrete set containing k ? 2 values (i.e., k "classes"). The definition is acquired by studying large collections of training examples of the form hx i ; f(x i )i. Existing approaches t ..."
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Cited by 104 (7 self)
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with distributed output codes such as those employed by Sejnowski and Rosenberg in the NETtalk system. This paper compares these three approaches to a new technique in which BCH errorcorrecting codes are employed as a distributed output representation. We show that these output representations improve
Results 1  10
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221