International Journal of Computer and Communication Technology
Article Title
MEASURING CODE QUALITY USING SUPPORT VECTOR MACHINE CLASSIFIER FOR IMPROVED CODING TECHNIQUES
Abstract
classification is the problem of identifying a set of categories to a new comments.To improve the efficiency of the code,quality metrics are applied for evaluation.The binary classifier,predicts the false positive rates with lesser accuracy,and limited number of classes only to predict the accuracy for classifier.To address this problem,support vector machine classifier is used,which helps in detecting the false positive rates,improving code quality and the accuracy will also increased.
Recommended Citation
IAVARASI, A.K. and AARTHY, S.
(2016)
"MEASURING CODE QUALITY USING SUPPORT VECTOR MACHINE CLASSIFIER FOR IMPROVED CODING TECHNIQUES,"
International Journal of Computer and Communication Technology: Vol. 7:
Iss.
4, Article 2.
DOI: 10.47893/IJCCT.2016.1374
Available at:
https://www.interscience.in/ijcct/vol7/iss4/2
DOI
10.47893/IJCCT.2016.1374
