Machine Learning Algorithm to Identify the Fault Data Identification Using Multi-Class Support Vector Machine

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Dr. R. Rajesh Kanna

Abstract

An experiment was conducted to the raw web log files, in a controlled lab environment, by using KDD technique and M-SVM algorithm. Based on the experiment conducted, the M-SVM algorithm generates 98.68% for true positive rate and 1.32% for false positive rate which indicates the significant efficiency of the new web log file classification and data transformation technique used in this research work. MSVM model identified fault data identification in more accurate with less time when compared to existing SVM model.

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How to Cite
, D. R. R. K. (2017). Machine Learning Algorithm to Identify the Fault Data Identification Using Multi-Class Support Vector Machine. International Journal on Future Revolution in Computer Science &Amp; Communication Engineering, 3(12), 471–475. Retrieved from http://www.ijfrcsce.org/index.php/ijfrcsce/article/view/1709
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