不平衡数据的分类问题是机器学习研究领域的重要问题, 有着广泛的应用, 如软件模块缺陷检测.
基于支持向量机的不平衡数据分类方法是主流的分类方法之一, 受到研究者广泛的关注 …

Software defect prediction (DP) is one of the most active research areas in software
engineering. DP models can provide error-prone source code components or changes, etc …

As a kernel-based method, whether the selected kernel matches the data determines the
performance of support vector machine. Conventional support vector classifiers are not …

Regression techniques have been applied to improve software quality by using software
metrics to predict defect numbers in software modules. This can help developers allocate …

Abstract Support Vector Machine (SVM) has been widely developed for tackling
classification problems. Imbalanced data exist in many practical classification problems …

In many classification problems, the class distribution is imbalanced. Learning from the
imbalance data is a remarkable challenge in the knowledge discovery and data mining field …

Software defect predictors are useful to maintain the high quality of software products
effectively. The early prediction of defective software modules can help the software …

In the software assurance process, it is crucial to prevent a program with defected modules
to be published to users since it can save the maintenance cost and increase software …

In order to solve the problems of traditional SVM classifier for software defect prediction, this
paper proposes a novel dynamic SVM method based on improved cost-sensitive SVM …

Support vector machines (SVM) have been used successfully in many classification
problems. But many classification tasks involve imbalanced training examples in practice …