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Software Defect Prediction Based on SMOTE-Tomek and XGBooste introduce a classification model that combines SMOTE-Tomek sampling and ensemble learning algorithm XGBoost. Our initial experimental results on ten NASA software defect datasets indicate a clear superiority of the proposed techniques when compared to other hybrid model regarding various assessment metrics, such Accuracy, F-Measure, and AUC.

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4.2 The Pechenga Greenstone Beltreenstone Belt. In an attempt to resolve the terminology, Melezhik (1996) suggested the name Transfennoscandian Greenstone Belt (Fig. 3.1); however, it remains to be seen whether or not this will be used in practice.