Efficient Implementation of Class Based Decomposition Schemes for Naive Bayes Classifier
International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Fully Refereed | Open Access | Double Blind Peer Reviewed

ISSN: 2319-7064


Downloads: 124 | Views: 362

M.Tech / M.E / PhD Thesis | Computer Science & Engineering | India | Volume 4 Issue 11, November 2015 | Popularity: 6.6 / 10


     

Efficient Implementation of Class Based Decomposition Schemes for Naive Bayes Classifier

Lateefa Shaik, N. Narasimha Swamy


Abstract: The accuracy of a Naive Bayes Classifier over text classification tasks can be significantly improved by taking advantage of decomposition schemes such as Error-Correcting Output Codes. ECOC is the task of document categorization and it is a method for decomposing multi-way classification problems into binary classification tasks. By The Additive nature of the classifier all binary classifiers can be trained in single pass through the data, through this approach the training complexity is reduces O (n. t. g) to O ( (n+t). g).


Keywords: ECOC, BCH, Naive Bayes Classifier


Edition: Volume 4 Issue 11, November 2015


Pages: 237 - 240



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Lateefa Shaik, N. Narasimha Swamy, "Efficient Implementation of Class Based Decomposition Schemes for Naive Bayes Classifier", International Journal of Science and Research (IJSR), Volume 4 Issue 11, November 2015, pp. 237-240, https://www.ijsr.net/getabstract.php?paperid=NOV151091, DOI: https://www.doi.org/10.21275/NOV151091

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