no code implementations • 25 Feb 2024 • Ahmed E. Hassan, Dayi Lin, Gopi Krishnan Rajbahadur, Keheliya Gallaba, Filipe R. Cogo, Boyuan Chen, Haoxiang Zhang, Kishanthan Thangarajah, Gustavo Ansaldi Oliva, Jiahuei Lin, Wali Mohammad Abdullah, Zhen Ming Jiang
Finally, we (i) show how the unique properties of FMArts enabled us to design and develop a complex FMware for a large customer in a timely manner and (ii) discuss the lessons that we learned in doing so.
1 code implementation • 18 Jan 2024 • Hao Li, Gopi Krishnan Rajbahadur, Dayi Lin, Cor-Paul Bezemer, Zhen Ming, Jiang
This classifier is then used to detect if a trained model is overfit.
no code implementations • 12 Feb 2022 • Gopi Krishnan Rajbahadur, Shaowei Wang, Yasutaka Kamei, Ahmed E. Hassan
We find that: i) Random forest based classifiers outperform other classifiers (best AUC) for both classifier building approaches; ii) In contrast to common practice, building a defect classifier using discretized defect counts (i. e., discretized classifiers) does not always lead to better performance.
no code implementations • 12 Feb 2022 • Gopi Krishnan Rajbahadur, Shaowei Wang, Yasutaka Kamei, Ahmed E. Hassan
Researchers usually discretize a continuous dependent variable into two target classes by introducing an artificial discretization threshold (e. g., median).
no code implementations • 4 Feb 2022 • Yingzhe Lyu, Gopi Krishnan Rajbahadur, Dayi Lin, Boyuan Chen, Zhen Ming, Jiang
Artificial Intelligence for IT Operations (AIOps) has been adopted in organizations in various tasks, including interpreting models to identify indicators of service failures.
no code implementations • 4 Feb 2022 • Gopi Krishnan Rajbahadur, Shaowei Wang, Yasutaka Kamei, Ahmed E. Hassan
We further observe that the commonly used defect datasets are rife with feature interactions and these feature interactions impact the computed feature importance ranks of the CS methods (not the CA methods).
1 code implementation • 4 Feb 2022 • Boyuan Chen, Mingzhi Wen, Yong Shi, Dayi Lin, Gopi Krishnan Rajbahadur, Zhen Ming, Jiang
However, DL models are challenging to be reproduced due to issues like randomness in the software (e. g., DL algorithms) and non-determinism in the hardware (e. g., GPU).
no code implementations • 3 Nov 2021 • Gopi Krishnan Rajbahadur, Erika Tuck, Li Zi, Dayi Lin, Boyuan Chen, Zhen Ming, Jiang, Daniel M. German
Publicly available datasets are one of the key drivers for commercial AI software.