IEICE TRANSACTIONS on Information
Active Learning for Software Defect Prediction
Summary :
An active learning method, called Two-stage Active learning algorithm (TAL), is developed for software defect prediction. Combining the clustering and support vector machine techniques, this method improves the performance of the predictor with less labeling effort. Experiments validate its effectiveness.
- Publication
- IEICE TRANSACTIONS on Information Vol.E95-D No.6 pp.1680-1683
- Publication Date
- 2012/06/01
- Publicized
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.E95.D.1680
- Type of Manuscript
- LETTER
- Category
- Software Engineering
Authors
Keyword
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Guangchun LUO, Ying MA, Ke QIN, "Active Learning for Software Defect Prediction" in IEICE TRANSACTIONS on Information,
vol. E95-D, no. 6, pp. 1680-1683, June 2012, doi: 10.1587/transinf.E95.D.1680.
Abstract: An active learning method, called Two-stage Active learning algorithm (TAL), is developed for software defect prediction. Combining the clustering and support vector machine techniques, this method improves the performance of the predictor with less labeling effort. Experiments validate its effectiveness.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.E95.D.1680/_p
Copy
@ARTICLE{e95-d_6_1680,
author={Guangchun LUO, Ying MA, Ke QIN, },
journal={IEICE TRANSACTIONS on Information},
title={Active Learning for Software Defect Prediction},
year={2012},
volume={E95-D},
number={6},
pages={1680-1683},
abstract={An active learning method, called Two-stage Active learning algorithm (TAL), is developed for software defect prediction. Combining the clustering and support vector machine techniques, this method improves the performance of the predictor with less labeling effort. Experiments validate its effectiveness.},
keywords={},
doi={10.1587/transinf.E95.D.1680},
ISSN={1745-1361},
month={June},}
Copy
TY - JOUR
TI - Active Learning for Software Defect Prediction
T2 - IEICE TRANSACTIONS on Information
SP - 1680
EP - 1683
AU - Guangchun LUO
AU - Ying MA
AU - Ke QIN
PY - 2012
DO - 10.1587/transinf.E95.D.1680
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E95-D
IS - 6
JA - IEICE TRANSACTIONS on Information
Y1 - June 2012
AB - An active learning method, called Two-stage Active learning algorithm (TAL), is developed for software defect prediction. Combining the clustering and support vector machine techniques, this method improves the performance of the predictor with less labeling effort. Experiments validate its effectiveness.
ER -
English
