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• W2939898614 abstract "While prior object-oriented software maintainability literature acknowledges the role of machine learning techniques as valuable predictors of potential change, the most suitable technique that achieves consistently high accuracy remains undetermined. With the objective of obtaining more consistent results, an ensemble technique is investigated to advance the performance of the individual models and increase their accuracy in predicting software maintainability of the object-oriented system. This paper describes the research plan for predicting object-oriented software maintainability using ensemble techniques. First, we present a brief overview of the main research background and its different components. Second, we explain the research methodology. Third, we provide expected results. Finally, we conclude summary of the current status." @default.
• W2939898614 created "2019-04-25" @default.
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• W2939898614 date "2019-04-15" @default.
• W2939898614 modified "2023-10-16" @default.
• W2939898614 title "Application of Ensemble Techniques in Predicting Object-Oriented Software Maintainability" @default.
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• W2939898614 doi "https://doi.org/10.1145/3319008.3319716" @default.
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