计算机科学 ›› 2016, Vol. 43 ›› Issue (7): 186-190.doi: 10.11896/j.issn.1002-137X.2016.07.034
熊婧,高岩,王雅瑜
XIONG Jing, GAO Yan and WANG Ya-yu
摘要： 将Adaboost算法应用到软件缺陷预测模型中是软件缺陷预测的一种新思路,Adaboost算法原理通过训练多个弱分类器构成一个更强的级联分类器,有效地避免了过拟合问题。通过采用美国国家航空航天局(NASA)的软件缺陷数据库的仿真实验,分别对原始BP神经网络算法和Adaboost算法进行分析对比,其中Adaboost的弱分类器采用神经网络。实验结果表明,Adaboost级联分类器有效地提高了软件缺陷预测模型的预测性能。
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