Machine Learning Approaches for Software Defect Prediction
Shaheen Layaq
Broschiertes Buch

Machine Learning Approaches for Software Defect Prediction

Balancing and Classification Techniques

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In today's data-driven world, most real-world applications face the challenge of class imbalance, where critical data is rare. This imbalance severely affects the accuracy of classification models, especially in sensitive domains like medical diagnosis, finance, and software defect prediction. In software systems, early defect prediction is essential for reducing cost and improving reliability. However, many machine learning models fail due to skewed datasets. To address this, we propose three novel algorithms: IDROS (oversampling), IDRUS (undersampling), and a hybrid approach IDROSUS. IDROS u...