IEICE TRANSACTIONS on Information
Kernel Based Asymmetric Learning for Software Defect Prediction
Summary :
A kernel based asymmetric learning method is developed for software defect prediction. This method improves the performance of the predictor on class imbalanced data, since it is based on kernel principal component analysis. An experiment validates its effectiveness.
- Publication
- IEICE TRANSACTIONS on Information Vol.E95-D No.1 pp.267-270
- Publication Date
- 2012/01/01
- Publicized
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.E95.D.267
- Type of Manuscript
- LETTER
- Category
- Software Engineering
Authors
Keyword
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Ying MA, Guangchun LUO, Hao CHEN, "Kernel Based Asymmetric Learning for Software Defect Prediction" in IEICE TRANSACTIONS on Information,
vol. E95-D, no. 1, pp. 267-270, January 2012, doi: 10.1587/transinf.E95.D.267.
Abstract: A kernel based asymmetric learning method is developed for software defect prediction. This method improves the performance of the predictor on class imbalanced data, since it is based on kernel principal component analysis. An experiment validates its effectiveness.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.E95.D.267/_p
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@ARTICLE{e95-d_1_267,
author={Ying MA, Guangchun LUO, Hao CHEN, },
journal={IEICE TRANSACTIONS on Information},
title={Kernel Based Asymmetric Learning for Software Defect Prediction},
year={2012},
volume={E95-D},
number={1},
pages={267-270},
abstract={A kernel based asymmetric learning method is developed for software defect prediction. This method improves the performance of the predictor on class imbalanced data, since it is based on kernel principal component analysis. An experiment validates its effectiveness.},
keywords={},
doi={10.1587/transinf.E95.D.267},
ISSN={1745-1361},
month={January},}
Copy
TY - JOUR
TI - Kernel Based Asymmetric Learning for Software Defect Prediction
T2 - IEICE TRANSACTIONS on Information
SP - 267
EP - 270
AU - Ying MA
AU - Guangchun LUO
AU - Hao CHEN
PY - 2012
DO - 10.1587/transinf.E95.D.267
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E95-D
IS - 1
JA - IEICE TRANSACTIONS on Information
Y1 - January 2012
AB - A kernel based asymmetric learning method is developed for software defect prediction. This method improves the performance of the predictor on class imbalanced data, since it is based on kernel principal component analysis. An experiment validates its effectiveness.
ER -
English
