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A Classification of Appendicitis Disease in Children Using SVM with KNN Imputation and SMOTE Approach
This study evaluates the effect of SMOTE and KNN imputation techniques on the
performance of SVM classification models on a nearly balanced dataset. The results show …
performance of SVM classification models on a nearly balanced dataset. The results show …
Analysis of Important Features in Software Defect Prediction using Synthetic Minority Oversampling Techniques (SMOTE), Recursive Feature Elimination (RFE) and …
Abstract Software Defect Prediction (SDP) is essential for improving software quality during
testing. As software systems grow more complex, accurately predicting defects becomes …
testing. As software systems grow more complex, accurately predicting defects becomes …
Software defect prediction based on support vector machine optimized by reverse differential chimp optimization algorithm
LF Chen, SP Zhang, YY Qin, KX Cao, T Du… - International Journal of …, 2025 - Springer
As software development becomes increasingly complex, defect prediction plays a crucial
role in ensuring software quality. Existing software defect prediction methods face limitations …
role in ensuring software quality. Existing software defect prediction methods face limitations …
Optimization of Backward Elimination for Software Defect Prediction with Correlation Coefficient Filter Method
Detecting software defects is a crucial step for software development not only to reduce cost
and save time, but also to mitigate more costly losses. Backward Elimination is one method …
and save time, but also to mitigate more costly losses. Backward Elimination is one method …
[PDF][PDF] Effect of SMOTE Variants on Software Defect Prediction Classification Based on Boosting Algorithm
Detecting software defects early on is critical for avoiding significant financial losses.
However, building accurate software defect prediction models can be challenging due to …
However, building accurate software defect prediction models can be challenging due to …