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    KAEA: A Novel Three-Stage Ensemble Model for Software Defect Prediction

    Nana Zhang1, Kun Zhu1, Shi Ying1, *, Xu Wang2

    CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 471-499, 2020, DOI:10.32604/cmc.2020.010117

    Abstract Software defect prediction is a research hotspot in the field of software engineering. However, due to the limitations of current machine learning algorithms, we can’t achieve good effect for defect prediction by only using machine learning algorithms. In previous studies, some researchers used extreme learning machine (ELM) to conduct defect prediction. However, the initial weights and biases of the ELM are determined randomly, which reduces the prediction performance of ELM. Motivated by the idea of search based software engineering, we propose a novel software defect prediction model named KAEA based on kernel principal component analysis… More >

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