The Empirical Study of Semi-Supervised Deep Fuzzy C-Mean Clustering for Software Fault Prediction
Software fault prediction is a very consequent research topic for software quality assurance. The performance of fault prediction model depends on the features that are used to train it. Redundant and irrelevant features can hinder the performance of a classification model. In this paper, we propose...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2018-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/8439927/ |