OPABP-Optimizing Parameters, to Improve Accuracy in Bug Prediction using Machine Learning-Reference-Cited by-同舟云学术

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OPABP-Optimizing Parameters, to Improve Accuracy in Bug Prediction using Machine Learning

Published:2022-12-09 Issue: Volume: Page:
ISSN:
Container-title:2022 4th International Conference on Artificial Intelligence and Speech Technology (AIST)
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Author:

Srivastava Nidhi¹,Agarwal Manisha¹,Arora Sapna²,Lamba Tripti³

Affiliation:

1. Banasthali Vidyapith,CSE,Rajasthan,India

2. IILM University,CSE,Gurugram,India

3. MAIT,CSE,Delhi,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10064684/10064724/10064852.pdf?arnumber=10064852

Reference32 articles.

1. Software defect prediction using cost-sensitive neural network

2. NASA/WVU Software Research Laboratory, 1995;sabolish,1995

3. Understanding the automated parameter optimization on transfer learning for cross-project defect prediction

4. Improving high-impact bug report prediction with combination of interactive machine learning and active learning

5. Comparative Analysis of Decision Tree Algorithms

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