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Full-Text Articles in Computer Engineering
Stability And Classification Performance Of Feature Selection Techniques, Huanjing Wang, Taghi Khoshgoftaar, Qianhui Liang
Stability And Classification Performance Of Feature Selection Techniques, Huanjing Wang, Taghi Khoshgoftaar, Qianhui Liang
Computer Science Faculty Publications
Feature selection techniques can be evaluated based on either model performance or the stability (robustness) of the technique. The ideal situation is to choose a feature selec- tion technique that is robust to change, while also ensuring that models built with the selected features perform well. One domain where feature selection is especially important is software defect prediction, where large numbers of met- rics collected from previous software projects are used to help engineers focus their efforts on the most faulty mod- ules. This study presents a comprehensive empirical ex- amination of seven filter-based feature ranking techniques (rankers) applied to …
Classification For Mass Spectra And Comprehensive Two-Dimensional Chromatograms, Xue Tian
Classification For Mass Spectra And Comprehensive Two-Dimensional Chromatograms, Xue Tian
Department of Computer Science and Engineering: Dissertations, Theses, and Student Research
Mass spectra contain characteristic information regarding the molecular structure and properties of compounds. The mass spectra of compounds from the same chemically related group are similar. Classification is one of the fundamental methodologies for analyzing mass spectral data. The primary goals of classification are to automatically group compounds based on their mass spectra, to find correlation between the properties of compounds and their mass spectra, and to provide a positive identification of unknown compounds.
This dissertation presents a new algorithm for the classification of mass spectra, the most similar neighbor with a probability-based spectrum similarity measure (MSN-PSSM). Experimental results demonstrate …
Design And Implementation Of A Byzantine Fault Tolerance Framework For Non-Deterministic Applications, H. Zhang, Wenbing Zhao, Louise E. Moser, P. Michael Melliar-Smith
Design And Implementation Of A Byzantine Fault Tolerance Framework For Non-Deterministic Applications, H. Zhang, Wenbing Zhao, Louise E. Moser, P. Michael Melliar-Smith
Electrical and Computer Engineering Faculty Publications
State-machine-based replication is an effective way to increase the availability and dependability of mission-critical applications. However, all practical applications contain some degree of non-determinism. Consequently, ensuring strong replica consistency in the presence of application non-determinism has been one of the biggest challenges in building dependable distributed systems. In this Study, the authors propose a classification of common types of application non-determinism with respect to the requirement of achieving Byzantine fault tolerance (BFT), and present the design and implementation of a BFT framework that controls these types of non-determinism in a systematic manner.