The Significant Effects of Data Sampling Approaches on Software Defect Prioritization and Classification
© 2017 IEEE. Context: Recent studies have shown that performance of defect prediction models can be affected when data sampling approaches are applied to imbalanced training data for building defect prediction models. However, the magnitude (degree and power) of the effect of these sampling methods...
Saved in:
Main Authors: | Kwabena Ebo Bennin, Jacky Keung, Akito Monden, Passakorn Phannachitta, Solomon Mensah |
---|---|
Format: | Conference Proceeding |
Published: |
2018
|
Subjects: | |
Online Access: | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85042378748&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/57025 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Chiang Mai University |
Similar Items
-
The Significant Effects of Data Sampling Approaches on Software Defect Prioritization and Classification
by: Kwabena Ebo Bennin, et al.
Published: (2018) -
MAHAKIL:Diversity based Oversampling Approach to Alleviate the Class Imbalance Issue in Software Defect Prediction
by: Kwabena Ebo Bennin, et al.
Published: (2018) -
MAHAKIL: Diversity Based Oversampling Approach to Alleviate the Class Imbalance Issue in Software Defect Prediction
by: Kwabena Ebo Bennin, et al.
Published: (2018) -
MAHAKIL: Diversity based oversampling approach to alleviate the class imbalance issue in software defect prediction
by: Kwabena E. Bennin, et al.
Published: (2018) -
MAHAKIL:Diversity based Oversampling Approach to Alleviate the Class Imbalance Issue in Software Defect Prediction
by: Ebo Bennin K., et al.
Published: (2017)