Kernel CCA Based Transfer Learning for Software Defect Prediction
نویسندگان
چکیده
An transfer learning method, called Kernel Canonical Correlation Analysis plus (KCCA+), is proposed for heterogeneous Crosscompany defect prediction. Combining the kernel method and transfer learning techniques, this method improves the performance of the predictor with more adaptive ability in nonlinearly separable scenarios. Experiments validate its effectiveness. key words: machine learning, defect prediction, transfer learning, kernel canonical correlation analysis
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ورودعنوان ژورنال:
- IEICE Transactions
دوره 100-D شماره
صفحات -
تاریخ انتشار 2017