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Using Error-Correcting Codes for Text Classification

Overview This paper explores in detail the use of Error Correcting Output Coding (ECOC) for learning text classifiers. The paper shows that the accuracy of a Naive Bayes Classifier over text classification tasks can be significantly improved by taking advantage of the error-correcting properties of the code. The paper also explores the use of different kinds of codes, namely Error-Correcting Codes, Random Codes, and Domain and Data-specific codes and gives experimental results for each of them.

Further White Paper Details
PublisherAccenture File FormatPDF, requires Acrobat Rdr 5
Date PublishedApril 2002 Downloads6
FormatWhite Papers   
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