On the Effectiveness of Cost Sensitive Neural Networks for Software Defect Prediction

K. Muthukumaran; Amrita Dasgupta; Shirode Abhidnya; Lalita Bhanu Murthy Neti

doi:10.1007/978-3-319-60618-7_55

ScienceGate Book Chapters

BOOK-CHAPTER

On the Effectiveness of Cost Sensitive Neural Networks for Software Defect Prediction

K. Muthukumaran Amrita Dasgupta Shirode Abhidnya Lalita Bhanu Murthy Neti

Year: 2017 Advances in intelligent systems and computing Pages: 557-570 Publisher: Springer Nature

DOI: 10.1007/978-3-319-60618-7_55

Get Full-Text PDF Get Analytical Report

Keywords:

Decision tree Computer science Artificial neural network Boosting (machine learning) Naive Bayes classifier Random forest Machine learning Software bug Artificial intelligence Bayes' theorem Logistic regression Software Bayesian probability Data mining Bayesian network Regression Statistics Support vector machine Mathematics

Metrics

Cited By

0.90

FWCI (Field Weighted Citation Impact)

Refs

0.75

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Software Engineering Research

Physical Sciences → Computer Science → Information Systems

Software Reliability and Analysis Research

Physical Sciences → Computer Science → Software

Software System Performance and Reliability

Physical Sciences → Computer Science → Computer Networks and Communications

On the Effectiveness of Cost Sensitive Neural Networks for Software Defect Prediction

Metrics

Citation History

Topics

Related Documents

Cost-sensitive boosting neural networks for software defect prediction

Software defect prediction using cost-sensitive neural network

Software defect prediction via cost-sensitive Siamese parallel fully-connected neural networks

Misclassification Cost-Sensitive Software Defect Prediction

Cost Sensitive Boosting Software Defect Prediction Method