Novel Software Effort Estimation Method using Naive Bayes Technique
S Harsha Vardhan Reddy, Kandasamy Thinakaran · 2022 3rd International Conference on Smart Electronics and Communication (ICOSEC) · 2022
Predict the effort needed to make the product with help of support vector machine and manipulating prediction accuracy with Naive Bayes. Support Vector Machine with sample size =20 and Naive Bayes with sample size =20 was iterated for predicting the accuracy with a Pre-power test about 80%. In Software effort Calculation the result value ofSupport Vector Machine and Naive Bayesis 84.37% and 73.23%. The statistical comparision in accuracy of two algorithms is 0.002 (p<0.05, 2-tailed) from samples tests. The Support Vector Machine got the result significantly have improvement than Naive Bayes in calculating the effor estimation.